multi-retranslation corpora: visibility, variation, value

Multi-Retranslation corporaVisibility variation value andvirtue

Tom Cheesman

Department of Languages Swansea University UK

Kevin Flanagan

Department of Languages Swansea University UK and SDL

Research Bristol UK

Stephan Thiel

Bauhaus University Weimar Germany and Studio Nand Berlin

Jan Rybicki

Institute of English Studies Jagiellonian University Poland

Robert S Laramee

Department of Computer Science Swansea University UK

Jonathan Hope

Department of English Strathclyde University UK

Avraham Roos

Amsterdam School of Culture and History University of

Amsterdam the Netherlands

AbstractVariation among human translations is usually invisible little understood andunder-valued Previous statistical research finds that translations vary most wherethe source items are most semantically significant or express most lsquoattitudersquo(affect evaluation ideology) Understanding how and why translations vary isimportant for translator training and translation quality assessment for culturalresearch and for machine translation development Our experimental projectbegan with the intuition that quantitative variation in a corpus of historicalretranslations might be used to project quasi-qualitative annotations onto thetranslated text We present a web-based system which enables users to createparallel segment-aligned multi-version corpora and provides visual interfacesfor exploring multiple translations with their variation projected onto a basetext The system can support any corpus of variant versions We report experi-ments using our tools (and stylometric analysis) to investigate a corpus of forty

Correspondence

Tom Cheesman Department

of Languages Swansea

University SA2 8PP UK

E-mail

tcheesmanswanseaacuk

Digital Scholarship in the Humanities Vol 32 No 4 2017 The Author 2016 Published by Oxford UniversityPress on behalf of EADHThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (httpcreativecommonsorglicensesby40) which permits unrestricted reuse distribution and reproduction in any medium provided the original work is properly cited

739

doi101093llcfqw027 Advance Access published on 23 August 2016Downloaded from httpsacademicoupcomdsharticle-abstract3247392669776by Swansea University useron 27 November 2017

German versions of a work by Shakespeare Initial findings lead to more ques-tions than answers

1 Introduction

Our project began with a simple observation and anintuition The observation in any set of multipletranslations in a given language variation amongthem varies through the course of the text Sometext units or chunks (at any level from word sayup to chapter or character part in a play) are morevariously translated than others The intuition thisvariation can be used to project an annotation ontothe translated text indicating where and how theextent of translation variation varies This is the es-sence of our online system It uses a lsquoTranslationArrayrsquo (a parallel multi-translation corpus alignedto a lsquobase textrsquo of the translated work) to achievelsquoVersion Variation Visualizationrsquo Here lsquoversionrsquoencompasses any text which can be at least partlyaligned with others But the website strapline islsquoExplore great works with their world-widetranslationsrsquo1

If multiple translations of a work exist then thework is enduringly popular andor prestigious ca-nonical or classic in the translating culture typicallylsquogreat worksrsquo of scripture literature philosophyetc2 Interest in comparing such worksrsquo multipletranslations is surprisingly limited Some largealigned retranslations corpora are publicly accessibleonline (works of scripture)3 but user access is lim-ited to two parallel texts and no analytic tools areprovided No similar resources exist for any secularworks at all yet This reflects the notorious lsquoinvisi-bilityrsquo of translators and translations in general(Venuti 2008) A key aim of our project is tomake them visible

Retranslations are successive translations of thelsquosamersquo source work often somehow dependent onprecursor (re)translations The source works con-cerned are mostly unstable texts in their originallanguage what translators translate varies andchanges And so does how they do it The gamutruns from word-for-word renderings to very freeadaptations or rewritings with little obvious relationto the source Relay translationmdashvia a third

languagemdashintroduces further variation If transla-tions are reprinted or otherwise re-used they tendto be changed again Venuti (2004) argues that re-translations (more than most translations) lsquocreatevaluersquo in the target culture4 A first translation of aforeign work creates awareness of it If retranslationsfollow the work becomes assimilated to the targetculture If retranslations multiply each both re-inforces the value and status of the work in thetarget culture and extends the range of competinginterpretations surrounding it Retranslations there-fore throw up questions going well beyond linguisticand cultural transfer concerning lsquothe values and in-stitutions of the translating culturersquo and how theseare defended challenged or changed (Venuti 2004p 106)

Within Translation Studies lsquoretranslation stu-diesrsquo is underdeveloped despite its fundamental im-portance for translation linguistics andcommunication as well as comparative trans-national cultural studies As Munday (2012)argues retranslations are important resources be-cause no single utterance or text exists in isolationfrom alternative forms it might have taken Anyextant text is surrounded by a lsquopenumbrarsquo of lsquoun-selected formsrsquo (Munday 2012 p 13 citing Grant2007 pp 183ndash4) so any translation is surroundedby lsquoshadow translationsrsquo (Johannson 2011 p 3citing Matthiessen 2001 p 83) Sets of translationsby different translators (or the same translators atdifferent moments) make visible at least someotherwise unselected forms This offers scope forstudying lsquothe value orientations that underlie theseselectionsrsquo (Munday 2012 p 13) Our project seeksto go even further from the how and why of vari-ation among translations back to the varying cap-acity of the translated text to provoke variation

The article is organized as follows Section 2 re-views related work including statistical studies intranslation variation Section 3 presents our soft-ware project covering our Aligner CorpusOverviews (including stylometric analysis) andour key innovation an interface deploying lsquoEddy

T Cheesman et al

740 Digital Scholarship in the Humanities Vol 32 No 4 2017

Downloaded from httpsacademicoupcomdsharticle-abstract3247392669776by Swansea University useron 27 November 2017

and Vivrsquo algorithms to explore translation variationSection 4 presents findings of experiments using thesoftware Section 5 offers concluding comments

2 Related Work

There has been little digital work on larger retrans-lations corpora involving works of wide intrinsicinterest and none designed to facilitate access tomultiple translations and the translated work to-gether with algorithmic analyses Janicke et al(2015) take in some ways a similar approach buttheir lsquoTRAVizrsquo interface offers a very different modeof text visualization is monolingual (shows notranslated text) and works best with more limitedvariation and shorter texts (see Section 33)Lapshinova-Koltunski (2013) describes a parallelmulti-translation corpus designed to support com-putational linguistic analyses of differences betweenprofessional translations student translationsMachine Translation (MT) outputs and editedMT outputs Shei and Pain (2002) proposed a simi-lar parallel corpus with an interface designed fortranslator training These projects only offer accessto filtered segments of the text corpus and do notenvisage exploring variation among retranslationsAltintas Can and Patton (2007) used two time-separated (c1950 c2000) collections of publishedtranslations of the same seven English French orRussian literary classics into Turkish to quantifyaspects of language change This raises the questionwhether such translations lsquorepresentrsquo their languageCorpus-based Translation Studies (Baker 1993Kruger et al 2011) has established that translatedlanguage differs from untranslated language Wealso know from decades of work in DescriptiveTranslation Studies (Morini 2014 Toury 2012)that retranslations vary for complex genre-market- subculture-specific and institutional fac-tors and individual psychosocial factors involvingthe translators and others with a hand in the work(commissioners editors) and their uses of re-sources including source versions and prior(re)translations

There is no consensus on defining such factorsand their interrelations The conclusion of a manual

analysis of eight English versions of Zolarsquos novelNana is typically vague

( ) specific conditions ( ) explain thesimilarities and differences ( ) The condi-tions comprise broad social forces changingideologies and changing linguistic literaryand translational norms as well as more spe-cific situational conditions the particular con-text of production and the translatorrsquospreferences idiosyncrasies and choices(Brownlie 2006 p 167)

The basic lesson is that translation is a humanitiessubject Translators are writers As Baker warns

Identifying linguistic habits and stylistic pat-terns is not an end in itself it is only worth-while if it tells us something about the culturaland ideological positioning of the translatoror of translators in general or about the cog-nitive processes and mechanisms that contrib-ute to shaping our translational behaviourWe need then to think of the potential motiv-ation for the stylistic patterns that mightemerge from this type of study(Baker 2000 p 258)

Her comment is cited by Li et al (2011 p 157)in their computationally assisted study of twoEnglish translations of Xueqin CaorsquosHongloumeng5 They conclude

corpus-assisted translation research can gobeyond proving the obvious or the alreadyknown as long as meta- or para-texts areavailable for the analysis The extent anddepth of such analysis of course depends onthe amount of information available in theform of meta- or other texts(Li et al 2011 p 164)

Genuine understanding of cultural materials re-quires knowledge and critical understanding ofmany other materials to assess how multi-scalehuman factors shape texts and the effects theyhave (had) in their cultural world

Non-digital studies in retranslation underline theimportance of such shaping factors Deane-Cox(2014) and OrsquoDriscoll (2011) both recently

Multi-retranslations

Digital Scholarship in the Humanities Vol 32 No 4 2017 741


investigated large sets of English retranslations of19th-century French novels They detail at lengththe historical contexts of each retranslation its pro-duction and reception and analyse short sampleslinguistically or stylistically Deane-Coxrsquos overall ar-gument disproves the lsquoRetranslation Hypothesisrsquoput forward by Antoine Berman (1990 p 1)Berman argued that over time successive retransla-tions should tend to translate the source text moreaccurately In factmdashas we will seemdashthis may holdfor a first few retranslations but when they multi-ply the hypothesis no longer holds This is partlybecause retranslators who come late in a series mustbe more inventive to distinguish their work fromthat of precursors and rivals The desire for distinc-tion is a great motivator (Mathijssen 2007 Hanna2016) Critical translation studies pays close atten-tion to such specific contextual factors viewing eachtranslation as an act of intervention in a particularmoment in a particular place in the geographicaland social world and a trace of a translatorrsquos (andassociated agentsrsquo) both conscious and unconsciouschoices (Munday 2012 p 20) As Munday arguestranslation is essentially an evaluative actTranslatorrsquos decisions are based on evaluations ofthe source text of the implicit values of its authorand intended audience and of the expectations andvalues of the intended audience of the translation

21 Statistical StudiesStatistical studies of differences between translationsconfirm this perspective and also rain on the MTparade They show that variation is greatest both inthe most semantically significant units of a text andin the units which are most expressive of values andaffect Babych and Hartley (2004) measured the sta-bility of alternative translations at word and phraselevel in English versions of 100 French news storiesby two professional translators They found a strongstatistical correlation between instability and thescores of linguistic items in the source text for sali-ence (tfidf score) or significance (S-score seeBabych et al 2003) The more important an itemis for a textrsquos meaning the less translators tend toagree about translating it (though each one is con-sistent in using their selected terms) Babych andHartley deduce that lsquohighly significant units

typically do not have ready translation solutionsand require some lsquolsquoartistic creativityrsquorsquo on the partof translatorsrsquo and that this necessary lsquofreedomrsquomakes translation fundamentally lsquolsquolsquonon-comput-ablersquorsquo or lsquolsquonon-algorithmicrsquorsquorsquo (Babych and Hartley2004 p 835 citing Penrose 1989) They concludethat there are

fundamental limits on using data-drivenapproaches to MT since the proper transla-tion for the most important units in a textmay not be present in the corpus of availabletranslations Discovering the necessary trans-lation equivalent might involve a degree ofinventiveness and genuine intelligence(Babych and Hartley 2004 p 836)

Munday (2012 pp 131ndash54) studied seventeenEnglish translations of an extract from a story byJorge Luis Borges two published translations andfifteen commissioned from advanced trainee trans-lators Four in five lexical units varied Invariancewas associated with lsquosimple basic experiential ordenotational processes participants and relationsrsquo(p 143) Variation mainly occurred in lsquolexical ex-pression of attitudersquo ie affectemotion judgmentethics appreciation or evaluation (p 24) Variationwas greatest at lsquocritical pointsrsquo where lsquoattitude-richrsquowords and phrases lsquocarry the attitudinal burden ofthe textrsquo and communicate lsquothe central axiologicalvalues of the protagonists narrator or writerrsquo(p 146)mdashagain in effect the semantically most sig-nificant items

Translations vary most at points of greatest se-mantic and evaluativeattitudinal salience MT has along way to go then Its problems include identify-ing attitude affect or evaluation in a text to betranslated In a chapter on MT and pragmaticsFarwell and Helmreich (2015) discuss lexical andsyntactic differences in 125 Spanish newswire art-icles translated into English by two professionaltranslators 40 of units differed and 41 of dif-ferences could be attributed to the translatorsrsquo dif-ferent lsquoassumptions about the worldrsquo (rather thanassumption-neutral paraphrasing or error) Oneexample is this headline

Acumulacion de vıveres por anuncios sısmicosen Chile

T Cheesman et al



Translation 1 Hoarding caused by earthquakepredictions in Chile

Translation 2 Stockpiling of provisions be-cause of predicted earthquakes in Chile(Farwell and Helmreich 2015 p 171)

The translations make vastly different ideolo-gical political evaluative assumptions lsquoHoardingrsquosuggests a panicky irrational population respond-ing to rumours of an unlikely event lsquoStockpilingrsquo(by the population or the civil authorities) is aprudent response to credible (scientific expertsrsquo)warnings It is impossiblemdashwithout lsquometa- orpara-textsrsquomdashto disentangle whether the translatorsimpute different values to the mind of the sourcetext creator or to its intended readers or to theanticipated readers of the target text andorwhether they express their own psychological andideological values lsquoAcumulacionrsquo here has majorevaluative implications which could not be pre-dicted without area-specific political and economicexpertise Perhaps a multi-retranslation corpuscould be used to discover which items provoke vari-ation as a proxy for such knowledge If not whatwould it discover

3 Project Description

A multi-retranslation corpus will contain versions ofvarious kinds complete fragmentary editedadapted versions versions derived from (a versionof) the original-language translated work or fromintermediaries in the translating language andorother languages versions in various media for vari-ous audiences (popular scholarly restricted) inmono- bi- or plurilingual formats from variousperiods and places produced and received undervarious economic political institutional and cul-tural-linguistic conditions An obvious lay questionis Which one is best But the problem is alreadyclear By what criteria or whose do we judgeModels for assessing professional translations(House 1997) are predicated on full and preciserendering of the source but work less well with cre-ative genres where such lsquofidelityrsquo is often subordi-nated to effect in the target culture Retranslationsof poetry plays novels religious or philosophical

works can be very successful (ie lsquogoodrsquo for manypeople) without being at all complete or accurate Arelated question is Why do most retranslations havebrief lives (just one publication or media or per-formance use) while othersmdashbacked by some insti-tutional authoritymdashbecome canonical and havemany editions revisions and re-uses over gener-ations Does the answer lie in linguistic textualqualities of the translation measured in terms ofits relation to the original work Or in some quali-ties of it measured in relation to alternative versionsor other target culture corpora Or does it lie solelyin institutional factors

Our project does not comprehensively addressthese questions It grew out of a particular piece oftranslation criticism and the intuition that digitaltools could be developed to explore patterns in vari-ation among multiple (re)translations in themselvesin relation to target cultural contexts and in relationto the translated work Before knowing any of theabove-mentioned studies Cheesman wanted to findways to compare a large collection of German trans-lations and adaptations of Shakespearersquos play TheTragedy of Othello The Moor of Venice (see corpusoverviews in section 32 below)6 His interest was as aresearcher in German and comparative literature andculture He had worked on a recent controversialversion of Othello (Cheesman 2010) and wonderedhow it related to others He manually examined overthirty translations (1766ndash2010) of a very smallsample a fourteen-word rhyming couplet a lsquocriticalmomentrsquo which is rich in affect evaluation and am-biguity (Cheesman 2011)7 His study showed howdifferences among the translations traced a 250-year-long conversation about human issues in the workmdashgender race class political power interpersonalpower and ethics Could digital tools help to exploresuch questions and communicate their interest to awider public The couplet he had selected was clearlymore variously translated than most passages inthe play So he wondered if we could devise an algo-rithmic analysis which would identify all the mostvariously translated passages to steer furtherresearch

A proof-of-concept toolset (lsquoTranslation ArrayPrototypersquo) was built using as test data a corpusof thirty-eight hand-curated digital texts of




German translations and adaptations of part of theplay Othello Act 1 Scene 3 This is about 3400continuous words of the playrsquos 28000 in English392 lines and 92 speeches (in Neillrsquos 2006 edition)The restricted sample size was due to restricted re-sources for curating transcriptions and translationcopyright limitations Versions were procured fromlibraries second-hand book-sellers and theatrepublishers (who distribute texts not availablethrough the book trade) Digital transcriptionstripped out original formatting and paratexts (pref-aces notes etc) The transcriptions were minimallyannotated marking up speech prefixes speechesand stage directions The brief for the programmers(Flanagan and Thiel) was to build visual web inter-faces enabling the user to align a set of versions witha base text and so create a parallel multi-versioncorpus8 obtain overviews of corpus metadata andaligned text data navigate parallel text displaysapply an algorithmic analysis to explore the differ-ing extent to which base text segments provoke vari-ation among translations customize this analysisand create various forms of data output to supportcultural analyses

31 AlignerAn electronic Shakespeare text was manually col-lated with a recent edition to give us a base textinclusive of historic variants9 Then we needed toalign it segmentally with the versions Existing opentools for working with text variants (eg Juxta col-lation software)10 lack necessary functionality so doexisting computer-assisted translation tools per-haps such software could be adapted at any ratewe built a web-based tool from scratch The devel-oper Flanagan explains its two main components

Ebla stores documents configuration detailssegment and alignment information calcu-lates variation statistics and renders docu-ments with segmentvariation informationPrism provides a web-based interface for up-loading segmenting and aligning documentsthen visualizing document relationshipsAreas of interest in a document are demar-cated using segments which also can benested or overlapped Each segment can

have an arbitrary number of attributes For aplay these might be lsquotypersquo (with values such aslsquoSpeechrsquo lsquoStage Directionrsquo) or lsquoSpeakerrsquo (withvalues such as lsquoOthellorsquo lsquoDesdemonarsquo) and soon

(Flanagan in Cheesman et al 2012)

Hand- or machine-made attributes such aslsquoironyrsquo lsquovariant from source xrsquo lsquocruxrsquo lsquobody partyrsquo lsquoaffect zrsquo lsquosyllogismrsquo lsquotrocheersquo and lsquoenjambe-mentrsquo are equally possible But all would requiretime-consuming tagging In fact we have workedonly with lsquotype Speechrsquo Segment positions arestored as character offsets within documents andtexts can be edited without losing this information(transcription errors keep being discovered)Segmented documents are aligned in an interactiveWYSIWYG tool where an lsquoauto-alignrsquo functionaligns all the next segments of specified attributeFor Othello every speech prefix speech and lsquootherrsquostring is automatically pre-defined as a segment ofthat type Any string of typographic characters in aspeech can be manually defined as a segment andaligned Thiel and colleagues at Studio Nand builtvisual interfaces on top of Prism including parallel-text views tailor-made for dramatic texts (base textand any translation) and the lsquoEddy and Vivrsquo viewdiscussed below (Section 4) Thiel (2014b) docu-ments the design process He also sketched a scal-able zoomable multi-parallel view of base text andall aligned versions an overview model which re-mains to be developed as an interface for combinedreading and analysis (Thiel 2014a)11

32 Corpus overviewsVisual overviews of a corpus support distant read-ings of text andor metadata features We devisedthree An online interactive time-map of historicalgeography shows when and where versions werewritten and published (performances are a desider-atum) it identifies basic genres (published books forreaders books for students theatre texts) and pro-vides bio-bibliographical information (Thiel 2012)A stylometric diagram is discussed in Section 322(Fig 2) lsquoAlignment mapsrsquo depict the informationcreated by segment alignment (Fig 1)

T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps

Alignment maps developed by Thiel are lsquobarcodersquo-type maps which show how a translationrsquos constitu-ent textual parts (here speeches) align with a similarmap of the base text Figure 1 shows thirty-five suchmaps in chronological sequence Each left-handblock represents the English base text of Othello13 the right-hand block represents a Germantext and the connecting lines represent alignmentsin the system Within each block horizontal barsrepresent speeches (in sequence top to bottom)and thickness represents their length measured inwords Othellorsquos longest speech in the scene (andthe play) is highlighted Small but significant differ-ences in overall length can be noticed translationstend to be longer than the translated texts so it isinteresting to spot versions which are complete yetmore concise such as Gundolf (1909) We can seewhich versions in which passages make cutsreduce expand transpose or add material whichcould not be aligned with the base text In thecentre of the figure the German translation(Felsenstein and Stueber 1964) of the Italian li-bretto (by Boito) of Verdirsquos opera Otello (1887) isa good example of omission addition and trans-position Omissions and additions are also evidentin the recent stage adaptations on the bottom lineZimmer (2007) like Boito assigns Othellorsquos longspeech to multiple speakers In our online systemthese maps serve as navigational tools alongside thetexts in Thielrsquos parallel-text views Each bar repre-senting a speech is also tagged with the relevantspeech prefix so any characterrsquos part can be high-lighted and examined Aligned segments are rapidlysmoothly synched in these interfaces assisting ex-ploratory bilingual reading

322 Stylometric network diagram

Figure 2 depicts a stylometric analysis of relativeMost Frequent Word frequencies in 7000-wordchunks of forty German versions of Othello carriedout by Rybicki using the Stylo script and the Gephivisualization tool12 The network diagram shows (1)relations of general similarity between versions rep-resented by relative proximity (clustering) and (2)similarities in particular sets of frequency countsrepresented by connecting lines their thickness or

strength represents degree of similarity These lines(edges) can indicate intertextual relations depend-ency of some kind including potential plagiarismDirectionality can be inferred from date labels onnodes For example the version by Bodenstedt(1867) (near top centre) was revised in the stronglyconnected version by Rudiger (1983) This confirmsdata on his title page Other results as we will seeare more surprising spurs to further research

The xy axes are not meaningful The analysisinvolves hundreds of counts using differing param-eters the diagram is a design solution to the prob-lem of representing high-dimensional data in a two-dimensional plane Removing or adding even oneversion produces a different layout and can re-ar-range clusters Moreover the analysis process is socomplex that we cannot specify which text featureslie behind the results Broadly though the diagramcan be read historically right to left a highly formalpoetic theatre language gives way to increasingly in-formal colloquial style

Nine versions are revisions editions or rewritingsof the canonical translation by Baudissin (originally1832 in the famed lsquoSchlegel-Tieckrsquo Shakespeare edi-tion see Sayer 2015) Most are quite strongly con-nected and closely clustered but the apparentstylometric variety is a surprise The long weakline connecting the cluster to the heavily revisedstage adaptation by Engel (1939) (upper left) is tobe expected but the length and weakness of theconnection with Wolffrsquos (1926) published edition(lower right) is more of a surprise His title pageindicated a modestly revised canonical text but styl-ometry suggests something more radical is goingon13

Above all this analysis reveals the salience of his-torical period Distinct clusters are formed by all theearly C19 versions (mid-right) arguably all the lateC19 versions (top) most of the late C20 versions(lower left) and all the C21 versions (far left) TheC21 versions are all idiosyncratic adaptations (cfFig 1 bottom line) It is surprising to see how simi-lar they appear in stylometric terms relative to therest of the corpus And what do the strong linksamong them indicate Mutual influence plagiarismcommon external influence What about the linesleading from Gundolf (1909) (low centre) across to

T Cheesman et al



Swaczynna (1972) to Laube (1978) to Gunther(1995) Gunther is the most celebrated livingGerman Shakespeare translator do these linestrace his debts to less famous precursors Periodoutliers are also interesting Zeynek (-1948) ap-pears to be writing a C19 style in the 1940s Theunknown Schwarz (1941) is curiously close to thefamous Fried (1972) Rothe (1956) (extreme bottomleft) is writing in a late C20 style in the 1950s Thisthrows interesting new light on the notorious lsquoRothecasersquo of the Weimar Republic and Nazi years he wasvictimized for his lsquoliberalrsquo lsquomodernrsquo approach totranslation (Von Ledebur 2002)

Genre is salient too A very distinct clusterbottom right includes all versions designed forstudy and written in prose (rather than verse)This includes our two earliest versions (1766 and1779) and two published 200 years later (19761985) Strongly interconnected weakly connectedwith any other versions this cluster demonstratesthe flaw in the approach of Altintas et al (2007)

Differences in the use of German represented bydistances across the rest of graph cannot be due toany general historical changes in the language Theyreflect changes in the specific ways German is usedby translators of Shakespeare for the stage andorfor publications aimed at people who want to readhis work for pleasure

33 The lsquoEddy and Vivrsquo interfaceOverviews are invaluable but the core of our systemis a machine for examining differences at smallscale The machine implements an algorithm wecalled lsquoEddyrsquo14 to measure variation in a corpusof translations of small text segments Eddyrsquos find-ings are then aggregated and projected onto the basetext segments by the algorithm lsquoVivrsquo (lsquovariation invariationrsquo) In an interface built by Thiel on thebasis of Flanaganrsquos work users view the scrollablebase text (Fig 3 left column) and can select anypreviously defined and aligned segment this callsup the translations of it in a scrollable list (Fig 3

Fig 2 Stylometric analysis of forty German OthellosNode label key Translator_Date Prefix Baud frac14 version of Baudissin (1832) Suffixes _Pr frac14 prose study edition Nosuffix frac14 other book _T frac14 theatre text (no book trade distribution) _X frac14 theatre text not performed (only version by awoman)




right columns) The list can be displayed in varioussequences (transition between sequences is a pleas-ingly smooth visual effect) by selecting from amenu order by date by the translatorrsquos surnameby length or (as shown in Fig 3) by Eddyrsquos algo-rithmic analysis of relative distinctiveness Eddymetrics are displayed with the translations andalso represented by a yellow horizontal bar whichis longer the higher the relative value

We defined lsquosegmentrsquo by default as a lsquonaturalrsquochunk of dramatic text an entire speech in semi-automated alignment Manual definition of seg-ments (any string within a speech) is possible butdefining and aligning such segments in forty ver-sions is time-consuming In future work we intendto use the more standard definition segment frac14sentence (not that this would simplify alignmentsince translation and source sentence divisions fre-quently do not match) Eddy compares the wordingof each segment version with a corpus word listhere the corpus is the set of aligned segment ver-sions No stop words are excluded no stemminglemmatization or parsing is performed Flanaganexplains how the default Eddy algorithm works

Each word in the corpus word list [the set ofunique words for all versions combined] is

considered as representing an axis in N-di-mensional space where N is the length ofthe corpus word list For each version apoint is plotted within this space whose co-ordinates are given by the word frequencies inthe version word list for that version (Wordsnot used in that version have a frequency ofzero) The position of a notional lsquoaveragersquotranslation is established by finding the cen-troid of that set of points An initial lsquoEddyrsquovariation value for each version is calculatedby measuring the Euclidean distance betweenthe point for that version and the centroidFlanagan in Cheesman et al (2012ndash13)

This default Eddy algorithm is based on thevector space model for information retrievalGiven a set S of versions a b c where eachversion is a set of tokens t1 t2 t3 tn we create aset U of unique tokens from all versions in S (ie acorpus word list) For each version in S we constructvectors of attributes A B C where each attributeis the occurrence count within that version of thecorresponding token in U that is

A frac14Xjajjfrac141

aj frac14 Ui

Fig 3 Eddy and Viv interface (Colour online)

T Cheesman et al



We construct a further vector Z to represent thecentroid of A B C such that

Z frac14Ai thorn Bi thorn Ci eth THORN

jSj

Then for a version a the default Eddy value iscalculated as

Eddy frac14

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiXjU jifrac141

jZi Aij2

vuut

This default Eddy formula is used in the experi-ments reported below coupled with a formula forViv as the average (arithmetic mean) of Eddy valuesOther versions of the formulae can be selected byusers15 eg an alternative Eddy value based on an-gular distance calculated as

Eddy frac142cos1 AZ

IAIIZ I

Work remains to be done on testing the differentalgorithms including the necessary normalizationfor variations in segment length16

Essentially Eddy assigns lower metrics to word-ings which are closer to the notional average andhigher metrics to more distant ones So Eddy ranksversions on a cline from low to high distinctivenessor originality or unpredictability It sorts common-or-garden translations from interestingly differentones

Viv shows where translators most and least dis-agree by aggregating Eddy values for versions of thebase text segment and projecting the result onto thebase text segment Viv metrics for segments are dis-played if the text is brushed and relative values areshown by a colour annotation (floor and ceiling canbe adjusted) As shown in Fig 3 the base text isannotated with a colour underlay of varying toneLighter tone indicates relatively low Viv (averageEddy) for translations of that segment Darkertone indicates higher Viv Shakespearersquos text cannow be read by the light of translations(Cheesman 2015)

Sometimes it is obvious why translators disagreemore or less In Fig 3 Roderigorsquos one-word speechlsquoIago -rsquo has a white underlay every version is the

same The Dukersquos couplet beginning lsquoIf virtue nodelighted beauty lack rsquo (the subject ofCheesmanrsquos initial studies) has the darkest under-lay As we knew translators (and editors per-formers and critics) interpret this couplet inwidely varying ways In the screenshot the Dukersquoscouplet has been selected by the user part of the listof versions can be seen on the right MTs back intoEnglish are provided not that they are alwayshelpful

Unlike the TRAViz system (Janicke et al 2015)ours does not represent differences between versionsin terms of edit distances and translation choices interms of dehistoricized decision pathways Oursystem preserves key cultural information (historicalsequence) It can better represent very large sets ofhighly divergent versions The TRAViz view of twolines from our Othello corpus (Janicke et al 2015Figure 17) is a bewilderingly complex graph Withhighly divergent versions of longer translation textsTRAViz output is scarcely readable Crucially thereis no representation of the translated base text TheEddy and Viv interface is (as yet) less adaptable toother tasks but better suited to curiosity-drivencross-language exploration17

4 Experiments with Eddy and Viv

41 Eddy and lsquoVirtue A figrsquoTo illustrate Eddyrsquos working Table 1 shows Eddyresults in simplified rank terms (lsquohighrsquo lsquolowrsquo orunmarked intermediate) for thirty-two chrono-logically listed versions of a manually aligned seg-ment with a very high Viv value lsquoVirtue A figrsquo(Othello 13315) An exclamation is always inMundayrsquos terms lsquoattitude-richrsquo burdened withaffect this one is a lsquocritical pointrsquo for several reasonslsquoVirtuersquo is a very significant term in the play andcrucially ambiguous in Shakespearersquos time it meantnot only lsquomoral excellencersquo but also lsquoessentialnaturersquo or lsquolife forcersquo and lsquomanlinessrsquo18 Thespeaker here is Iago responding to Roderigo whohas just declared that he cannot help loving theheroine Desdemona lsquo it is not in my virtue toamend itrsquo Roderigo means not in my nature mypower over myself my male strength But Iagorsquosresponse implies the moral meaning too Then




Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



the phrase lsquoA figrsquo is gross sexual innuendo lsquoFigrsquomeant vagina The expression derives fromSpanish and refers to an obscene hand gesture in-tense affect (see Neill 2006 p 235) (The expressionlsquoI donrsquot givecare a figrsquo was once commonplace andoften used euphemistically for lsquofuckrsquo a wordShakespeare never uses)

The lowest and highest seven Eddy rankings areindicated Eddyrsquos lowest-scoring translation islsquoTugend Quatschrsquo (16 26) lsquoTugendrsquo is themodern dictionary translation of (moral) lsquovirtuersquolsquoQuatschrsquo is a harmless expression of disagreementa bowdlerized translation (bowdlerization is clear inmost versions here)19 The Eddy score is low be-cause most translations (until 1985) use lsquoTugendrsquoand several also use lsquoQuatschrsquo Eddyrsquos highestscore is for lsquoCharakter Am Arsch der Charakterrsquo(30) This is Zaimoglursquos controversial adaptationof 2003 with which Cheesmanrsquos work on Othellobegan (2010) No other translation uses thosewords including the preposition lsquoamrsquo and articlelsquoderrsquo lsquoCharakterrsquo accurately translates the mainsense of Shakespearersquos lsquovirtuersquo here and lsquoArschrsquofairly renders lsquoA figrsquo This is among the philologic-ally informed translations of lsquovirtuersquo (as lsquoenergyrsquolsquostrengthrsquo lsquopowerrsquo) a series which begins withSchwarz (1941) (13) It is also among the syntac-tically expansive translations with colloquial speechrhythms which begin with Zeynek (-1948) (15)20

Both series become predominant following the pres-tigious Fried (1972) (21)

Reading versions both historically and withEddy in our interface makes for a powerful toolHere the historical distribution of Eddy rankingsconfirms what we already know about changes inShakespeare translation The lowest mostly appearup to 1926 The highest mostly appear since 1972(recall Figure 2 lower left quadrant) Ranking bylength in typographical characters is not oftenuseful but with such a short segment its resultsare interesting and similar to Eddyrsquos Most of theshortest are up to 1947 and most of the longestsince 1972 that shift towards more expansive col-loquial translations again

Similar historical Eddy results are found formany segments in our corpus An lsquoEddy Historyrsquograph plotting versionsrsquo average Eddy on a timeline

can be generated it shows Eddy average rising inthis corpus since about 1850 This may be a peculi-arity of German Shakespeare It may be an artefactof the method But it is conceivable that with fur-ther work the period of an unidentified translationmight be predicted by examining its Eddy metrics

Eddy and Viv results for any selected segmentsbased on the full corpus or a selected subset of ver-sions can be retrieved and explored in several formsof chart table and data export The interactivelsquoEddy Variationrsquo chart for example facilitates com-parisons between one translatorrsquos work and that ofany set of others (eg her precursors and rivals) Itplots Eddy results for selected versions against seg-ment position in the text any versionrsquos graph can bedisplayed or not (simplifying focus on the transla-tion of interest) when a node is brushed the rele-vant bilingual segment text is displayed

Eddyrsquos weaknesses are evident in Table 1 too Itfails to highlight the only one-word translation(29) or the one giving lsquofigrsquo for lsquofigrsquo (19) or theone with the German equivalent of lsquofuckrsquo (20) ex-pressing the obscenity which remains concealedfrom most German readers and audiences We stillneed to sort ordinary translations from extraordin-ary and innovative ones in more sophisticated waysEddy also fails to throw light directly on genetic andother intertextual relations Some are indicated inthe lsquoIntertextsrsquo column in Table 1 the probable in-fluence of some prestigious retranslations is appar-ent in several cases as is the possible influence ofsome obscure ones Such dependency relations re-quire different methods of analysis and representa-tion Stylometric analysis (Section 322) providespointers More advanced methods must also en-compass negative influence or significant non-imi-tation Table 1 showsmdashand this result is typicaltoomdashthat the canonical version (5) the mostoften read and performed German Shakespearetext from 1832 until today is lsquonotrsquo copied or evenclosely varied That is no doubt because of risk to aretranslatorrsquos reputation Retranslators must differ-entiate their work from what the public and thespecialists know (Hanna 2016)

The tool we built is a prototype Eddy is admit-tedly imperfect But its real virtue lies in the power itgives to Viv enabling us to investigate to what




extent base text features and properties might cor-relate with differences among translations Even thatis only a start as Flanagan points out

Ebla can be used to calculate different kinds ofvariation statistics for base text segmentsbased on aligned corpus content These canpotentially be aggregated-up for morecoarse-grained use The results can be navi-gated and explored using the visualizationfunctionality in Prism However translationvariation is just one of the corpus propertiesthat could be investigated Once aligned thedata could be analysed in many other ways(Flanagan in Cheesman et al 2012ndash13)

42 lsquoVivrsquo in VeniceAn initial Viv analysis of Othello 13 involving allthe ninety-two natural lsquospeechrsquo segments was re-ported (Cheesman 2015)21 It found that thelsquohighestrsquo Viv-value segments tended to be (1) nearthe start of the scene (2) spoken by the Duke ofVenice who dominates that scene but appears inno other and (3) rhyming couplets (rather thanblank verse or prose) There are twelve rhymingcouplets in the scene two are speech segmentsboth were in the top ten of ninety-two Viv resultsNo association was found between Viv value andperceptible attitudinal intensity or any linguisticfeatures We did find some high-Viv segments asso-ciated with specific cross-cultural translation chal-lenges Highest Viv was a speech by Iago with thephrase lsquosilly gentlemanrsquo which provokes many dif-ferent paraphrases But some lower-Viv segmentspresent similar difficulties on the face of it Therewas no clear correlation

Still four hypotheses emerged for furtherresearch

Hypothesis 1 Based on rhyming couplets havinghigh Viv-value retranslators diverge more whenthey have additional poetic-formal constraints22

Hypothesis 2 Based on finding (1) above retran-slators diverge more at the start of a text or majorchunk of text (ie at the start of a major task)

Hypothesis 3 Based on finding (2) above retran-slators diverge more in translating a very salientlocal text feature in a structural chunk (in thisscene the part of the Duke) and less in translating

global text features (eg here Othello DesdemonaIago)

Hypothesis 4 relates to lsquolowrsquo Viv findings It wassomehow disappointing to find that speeches by thehero Othello and the heroine Desdemona includingpassages which generate much editorial and criticaldiscussion had moderate low or very low Vivscores Famous passages where Othello tells his lifestory and how he fell in love with Desdemona orwhere Desdemona defies her father and insists ongoing to war with Othello surely present key chal-lenges for retranslators Perhaps passages which havebeen much discussed by commentators and editorspose less of a cognitive and interpretive challenge asthe options are clearly established23 This hypothesiscould be investigated by marking up passages with ametric based on the extent of associated annotationin editions andor frequency of citation in other cor-pora For now we have speculated that the herorsquosand heroinersquos speeches in this particular scene doexhibit common attitudinal not so much linguisticbut dramatic features In the low-Viv segments thecharacters can be seen to be taking care to expressthemselves particularly clearly even if very emo-tional they are controlling that emotion to controla dramatic situation Perhaps translators respond tothis lsquolow affectrsquo by writing less differently But it isdifficult to quantify such a text feature and so checkViv results against any lsquoground truthrsquo

There is another possible explanation in themost lsquocanonicalrsquo parts of the text (here the herorsquosand heroinersquos parts) retranslators perhaps tread acareful line between differentiating their work andlimiting their divergence from prestigious precur-sors24 Such lsquoprestige cringersquo would relate to theabove-mentioned negative influence or non-imita-tion of the most prestigious translations (Section34) Precursors act paradoxically as both negativeand positive constraints on retranslators

Hypothesis 4 in the most canonical constituentparts of a work Viv is low as retranslators tend tocombine willed distinctiveness with caution limit-ing innovation

In the initial analysis the groups of speeches as-signed highest and lowest Viv values had suspi-ciously similar lengths Clearly the normalizationof Eddy calculations for segment length leaves

T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)




something to be desired The next and latest analysisfocused on segments of similar length to investigateour hypotheses

43 lsquoVivrsquo in two linersTable 2 shows the grammatically complete two-lineverse passages in Othello 13 plus prose passages ofequivalent length25 in Viv value rank order A sub-corpus of twenty translations was selected for bettercomparability26 The text assigned to each majorcharacter part here is reasonably representative oftheir overall part in the scene counted in linesBrabantio (sample eighteen lines [nine couplets]total sixty-one lines) 03 Desdemona (1031) 032Duke (2267) 033 Iago (1465) 021 Othello (20108) 019

Hypothesis 1 seems to be confirmed thoughmore work needs to be done to prove it conclu-sively high Viv value correlates with poetic-formalconstraint In the column lsquoFormrsquo in Table 2 blankverse is the default Unsurprisingly rhyming coup-lets appear mostly in the top half of the tableincluding five of the top ten items Translatorsenjoy responding to the formal challenge of rhym-ing couplets in self-differentiating ways and theymust so respond or else they very obviously plagi-arize because these items are rare in the text andhighly noticeable for audiences or readers

Hypothesis 2 is not confirmed scanning thecolumn lsquoRunning orderrsquo there is no sign that trans-lators differentiate their work more at the start ofthe scene as they embark on a new chunk of thetask That could have been interesting for psycho-linguistic and cognitive studies of translation(Halverson 2008)

Hypothesis 3 seems to be confirmed but we needmuch more evidence to be sure we have discovereda general pattern Scanning the column lsquoSpeakerrsquothe Dukersquos segments are more variously translatedthan those of other speakers Even if we excluderhyming couplets the Duke is over-represented inthe upper part of the table Brabantio and Iago alsohave some very high-Viv lines but their segmentsare distributed evenly up and down the table Not sowith the Duke who is the salient local text featurein this scene and no other

Tab

le2

Co

nti

nu

ed

T Cheesman et al



Hypothesis 4 also seems provisionally confirmedOthello is strikingly low-Viv mostly Desdemonatends to be low- to mid-Viv Translations of theirparts differ lsquolessrsquo than other parts at this scale WhyWe do not know It could be lsquoprestige cringersquo(Section 42) But it could also be specific to thistext Othello in particular refuses lsquoaffectrsquo in thisscene as he does throughout the first half of theplay he is in command of everything includinghis emotions He echoes a much discussed linejust spoken by Desdemona (lsquoI saw Othellorsquos visagein his mindrsquo 13250) when he says to the Duke andassembled Senators that he wants her to go to warwith him but

I therefore beg it notTo please the palate of my appetiteNor to comply with heatmdashthe young affectsIn me defunctmdashand proper satisfactionBut to be free and bounteous to her mind( )(Othello 13258ndash63)

This is one of the playrsquos cruxesmdashpassages whicheditors deem corrupt and variously resolve (herelsquomersquo is often changed to lsquomyrsquo lsquodefunctrsquo to lsquodistinctrsquoand the punctuation revised)27 Translators also re-solve this passage variously depending in part onwhich edition(s) they work with butmdashas measuredby Vivmdashnot very variously compared with otherpassages Can it be that textual lsquoaffectrsquo is relativelyless because that is the kind of character the mindthe lsquovirtuersquo Othello is projecting

5 Concluding Comments

Findings which only confirmed what was alreadyknown would be truly disappointing (though wedo need some such confirmation to have anyfaith in digital tools) Digital literary studiesshould provoke thought A classic example isMorettirsquos discovery of a rhythm of 25ndash30 years inthe emergence and disappearance of C19 novelisticgenres which he uneasily ascribed to a cycle of bio-logical-sociocultural lsquogenerationsrsquo

I close on a note of perplexity faute de mieuxsome kind of generational mechanism seems

the best way to account for the regularity ofthe novelistic cyclemdashbut lsquogenerationrsquo is itself avery questionable concept Clearly we mustdo better(Moretti 2003 p 82)

So too with lsquoTranslation Arraysrsquo and lsquoVersionVariation Visualizationrsquo we must do better

We wanted to demonstrate that this sort of ap-proach opens up interesting possibilities for futureresearch28 Of course one big difference betweenMorettirsquos work and ours so far is one of scale Histeam works with tens or hundreds of thousands oftexts and metadata items We are working with afew dozen versions of one play in one target lan-guage because that is what we have got29 and only afragment of the play because we chose to make thetexts publicly accessible which entails copyright re-strictions (and some expense) Our approach re-quires time-consuming text curation (correction ofdigital surrogates against page images)30 permissionacquisition and manual segmentation and align-ment processes (more sophisticated approachesincluding machine learning will speed these up)31

Moretti experimentally lsquooperationalizesrsquo pre-digital critical concepts such as lsquocharacter-spacersquo orlsquotragic collisionrsquo (Moretti 2013) by measuringquantities in texts digital proxies or analoguesEddy and Viv on the other hand are measuringrelational corpus properties which have no obviouspre-digital analogue What could they be proxiesfor Eddy makes visible certain kinds of resemblanceand difference certain sequences patterns of influ-ence and distinctiveness Critically understandingthese still depends on understanding lsquopara- andmeta-textsrsquo (Li Zhang and Liu 2011) Vivrsquos contri-bution is even less certain we wonrsquot know whetherits results correspond to anything lsquorealrsquo about trans-lated textsrsquo qualities or those of translations or oftranslators until we have studied many more cases

Eddy and Viv analysis as implemented is crudeWe can imagine training next-generation Eddy onhuman-evaluated variant translations We can en-visage experiments with lemmatization stopwordexclusion parsing morphosyntactical tagging32 di-verse automated segment definitions text analyticsand plugging in other corpora for richer analysesWhen does a translatorrsquos use of language mimic a




pre-existing style when is it innovative in whatway We can map texts to Wordnets historical dic-tionaries and thesauri We can model topics analysesentiments We can explore consistency and coher-ence within translations usage of less commonwords word-classes word-sets grammatical rhet-orical poetic prosodic metrical metaphorical fea-tures and so on We can generate intertextual andphylogenetic trees We can perhaps adjust Viv forhistorical sequence and weight for the complex ef-fects of influence imitation and intentional non-imitation Given multi-lingual parallel corpora wecan project a cross-cultural Viv The more sophisti-cated the analysis the greater its scope the greaterthe cost of text preparation and annotation and thegreater the challenge in creating visual interfaceswhich offer value to non-programmers For text re-sources on a scale which might justify such invest-ment we must next look to scripture Then we willneed experts in Godrsquos domain as well

Funding

This work was supported by Swansea University(Research Incentive Fund and Bridging the Gaps)and the main phase of software development wasfunded by a 6-month Research DevelopmentGrant in 2012 under the Digital Transformationstheme of the Arts and Humanities ResearchCouncil (UK) reference AHJ0124831

ReferencesAlgee-Hewitt M Allison S Gemma M Heuser

R Moretti F and Walser H (2016) Canonarchive large-scale dynamics in the literary fieldLiterary Lab Pamphlet Vol 11 httplitlabstan-fordeduLiteraryLabPamphlet11pdf (accessed 16January 2016)

Altintas K Can F and Patton J M (2007) Languagechange quantification using time-separated paralleltranslations Literary and Linguistic Computing 22(4)375ndash93

Babych B and Hartley A (2004) Modelling legitimatetranslation variation for automatic evaluation of MTquality Proceedings of LREC 2004 pp 833ndash6 http

wwwlrec-conforgproceedingslrec2004pdf707pdf

(accessed 16 January 2016)

Babych B Hartley A and Atwell E (2003) Statistical

modelling of MT output corpora for information ex-

traction In Archer D Rayson P Wilson A and

McEnery T (eds) Proceedings of the Corpus

Linguistics 2003 Conference Lancaster University 28ndash

31 March 2003 pp 62ndash70 httpucrellancsacukpub-

licationsCL2003papersbabychpdf (accessed 16

January 2016)

Baker M (1993) Corpus linguistics and translation stu-

dies implications and applications In Baker M

Francis G and Tognini-Bonelli E (eds) Text and

Technology In Honour of John Sinclair Amsterdam

and Philadelphia John Benjamins pp 233ndash250

Baker M (2000) Towards a methodology for investigating

the style of a literary translator Target 12(2) 241ndash66

Baudissin W (1832) Shakspeares dramatische Werke

Vol 8 Berlin Reimer

Berman A (1990) La Retraduction comme espace de

traduction Palimpsestes 13 1ndash7

Bodenstedt F (1867) Othello der Mohr von Venedig

Leipzig Brockhaus

Bolte H and Hamblock D (1985) Othello Englisch-

Deutsch Stuttgart Philipp Reclam

Brownlie S (2006) Narrative theory and retranslation

theory Across Languages and Cultures 7(2) 145ndash70

Buhss W (1996) William Shakespeare Othello Venedigs

Neger Berlin Henschel Schauspiel Theaterverlag

Cheesman T (2010) Shakespeare and Othello in Filthy

Hell Zaimoglu and Senkelrsquos Politico-Religious

Tradaptation Forum for Modern Language Studies

46(2) 207ndash20

Cheesman T (2011) Thirty Times lsquoMore Fair Than

Blackrsquo Othello Re-translation as Political Re-statement

Angermion 4 1ndash52

Cheesman T (2015) Reading originals by the light of

translations Shakespeare Survey 68 87ndash98

Cheesman T (2016) Othello 13 lsquoFar More Fair Than

Blackrsquo In Smith B R (ed) The Cambridge Guide to

the Worlds of Shakespeare vol 2 The Worldrsquos

Shakespeare 1660-Present Cambridge Cambridge

University Press pp 1156ndash61

Cheesman T and the VVV Project Team (2012)

Translation Sorting with Eddy and Viv httpwww

scribdcomdoc101114673Eddy-and-Viv (accessed 16

January 2016)

T Cheesman et al



Cheesman T Flanagan K and Thiel S (2012ndash13)

Translation Array Prototype 1 Project Overview

httpwwwdelightedbeautyorgvvvclosedHome

Project (accessed 16 January 2016)

Cheesman T Flanagan K Thiel S and Rybicki J

(2016) Five maps of translations of Shakespeare In

Wiggin B and Macleod C (eds) UnTranslatables

New Maps for Germanic Literatures Evanston IL

Northwestern University Press forthcoming

Deane-Cox S (2014) Retranslation Literature and

Reinterpretation London Bloomsbury

Eder M Kestemont M and Rybicki J (2016)

Stylometry with R a package for computational text

analysis R Journal 16(1) forthcoming

Engel E (1939) William Shakespeare Othello Berlin

Felix Bloch Erben

Engler B (1976) Othello Englisch-deutsche

Studienausgabe Munich Franke

Farwell D and Helmreich S (2015) Pragmatics-based

machine translation In Chan S (ed) The Routledge

Encyclopedia of Translation Technology AbingdonNew

York Routledge pp 167ndash85

Felsenstein W and Stueber C (1964) Giuseppe Verdi

Othello Milan and Frankfurt am Main Ricordi

Flatter R (1952) Othello der Mohr von Venedig

Sonderabdruck fur Buhnenzwecke Munich Theater-

Verlag Desch

Fried E (1972) HamletOthello Berlin Wagenbach

Geng Z Laramee R S Cheesman T Ehrmann E

and Berry D M (2011) Visualizing translation vari-

ation Shakespearersquos Othello Advances in visual com-

puting Lecture Notes in Computer Science 6938 653ndash63

Geng Z Laramee RS Flanagan K Thiel S and

Cheesman T (2015) ShakerVis visual analysis of seg-

ment variation of German translations of Shakespearersquos

Othello Information Visualization 14(4) 273ndash88

Grant C B (2007) Uncertainty and Communication

New Theoretical Investigations Basingstoke Palgrave

Macmillan

Gundolf F (1909) Shakespeare in deutscher Sprache Vol

1 Berlin Bondi 1920

Gunther F (1995) William Shakespeare Othello

Zweisprachige Ausgabe Munich Deutscher

Taschenbuch Verlag

Hadas E (2015) Word2Dream A Readerrsquos Companion

httperanhadascomword2dream (accessed 16

January 2016)

Halverson S L (2008) Psycholinguistic and cognitive

approaches In Baker M and Saldanha G (eds)

Routledge Encyclopedia of Translation Studies London

and New York Routledge pp 211ndash16

Hanna S (2016) Bourdieu in Translation Studies The

Socio-cultural Dynamics of Shakespeare Translation in

Egypt London and New York Routledge

Hope J and Witmore M (2014) The language of

Macbeth In Thompson A (ed) Macbeth The State

of Play London Bloomsbury (Arden) pp 183ndash208

House J (1997) Translation Quality Assessment A Model

Revisited Tubingen Narr

Hutchings T (2015) Studying apps research

approaches to the digital Bible In Cheruvallil-

Contractor S and Shakkour S (eds) Digital

Methodologies in the Sociology of Religion London

Bloomsbury chapter 9

Janicke S Geszligner A Franzini G Terras M Mahony

S and Scheuermann G (2015) TRAViz a visualization

for variant graphs Digital Scholarship in the Humanities

30(Suppl 1) i83ndash99 httpdshoxfordjournalsorg

content30suppl_1i83 (accessed 16 January 2016)

Johannson S (2011) Between Scylla and Charybdis on

individual variation in translation Languages in

Contrast 11(1) 3ndash19

Kruger A Wallmach K and Munday J (2011)

Corpus-based Translation Studies Research and

Applications London Continuum

Lapshinova-Koltunski E (2013) VARTRA a compar-

able corpus for analysis of translation variation

Proceedings of the 6th Workshop on Building and

Using Comparable Corpora Sofia Bulgaria August 8

2013 pp 77ndash86 httpaclweborganthologyW13-

2510 (accessed 16 January 2016)

Laube H (1978) William Shakespeare Othello Der Mohr

von Venedig ubersetzt und bearbeitet Frankfurt am

Main Verlag der Autoren

Lauterbach E S (1973) William Shakespeare Othello

der Mohr von Venedig Aus dem Englischen von E S

Lauterbach unter Mitarbeit von Benita Gleisberg

Berlin Henschel Schauspiel Theaterverlag

Li D Zhang C and Liu K (2011) Translation style

and ideology a corpus-assisted analysis of two English

translations of Hongloumeng Literary and Linguistic

Computing 26(2) 153ndash166

Long L (2007) Revealing commentary through com-

parative textual analysis the realm of Bible translations

Palimpsestes 20 35ndash57




Matthiessen CMIM (2001) The environments of

translation In Steiner E and Yallop C (eds) Beyond

Content Exploring Translation and Multilingual Text

Production Berlin and New York Mouton de

Gruyter pp 41ndash124

Mathijssen J (2007) The Breach and the Observance

Theatre Retranslation as a Strategy of ArtisticDifferentiation with Special Reference to

Retranslations of Shakespearersquos Hamlet (1777-2001)

PhD dissertation Utrecht University

Moretti F (2003) Graphs maps trees abstract models

for literary history 1 New Left Review 24 67ndash93

Moretti F (2013) lsquoOperationalizingrsquo or the Function of

Measurement in Modern Literary Theory Literary Lab

Pamphlet 6 httplitlabstanfordeduLiteraryLabPamphlet6pdf (accessed 16 January 2016)

Morini M 2014 The Pragmatic Translator An Integral

Theory of Translation London Bloomsbury

Motschach H (1992) William Shakespeare Othello

Munich Drei Masken

Mueller M (2003-14) About Metadata and the Query

Potential of the Digital Surrogate httpwordhoard

northwesterneduusermanindexhtml (accessed 16

January 2016)

Munday J (2012) Evaluation in Translation Critical

Points of Translation Decision-making Abingdon NewYork Routledge

Neill M (ed) (2006) The Oxford Shakespeare Othello

Oxford Oxford University Press

OrsquoDriscoll K (2011) Retranslation through the Centuries

Jules Verne in English Oxford Peter Lang

Paloposki O and Koskinen K (2010) Reprocessing

texts the fine line between retranslating and revising

Across Languages and Cultures 11(1) 29ndash48

Penrose R (1989) The Emperorrsquos New Mind Concerning

Computers Minds and the Laws of Physics OxfordOxford University Press

Roos A (2015) Making a Clean Breast of English

Passover Haggadah Translations Data Visualization

of Bowdlerization in Haggadah Translations of

Ezekiel 167 Unpublished chapter of PhD dissertation

University of Amsterdam

Rothe H (1956) Der Elisabethanische Shakespeare Vol

4 Baden-Baden Holle

Rudiger R (1983) William Shakespeare Othello derMohr von Venedig Tragodie In Anlehnung an die

Ubersetzung von Friedrich von Bodenstedt Nach dem

Original neu ubersetzt Berlin Felix Bloch Erben

Rybicki J (2012) The great mystery of the (almost) in-

visible translator stylometry in translation In Oakley

M and Ji M (eds) Quantitative Methods in Corpus-

Based Translation Studies Amsterdam John Benjamins

pp 231ndash48

Rybicki J and Heydel M (2013) The stylistics and styl-

ometry of collaborative translation Woolfrsquos lsquoNight and

Dayrsquo in Polish Literary and Linguistic Computing

28(4) 708ndash17

Sayer J (2015) Wolf Graf Baudissin (1789-1878) Life and

Legacy Munster LIT

Schaller R (1959) Shakespeares Werke Vol 4 Berlin

Rutten amp Loening

Schroder R A (1962) Shakespearedeutsch Berlin

Frankfurt am Main Suhrkamp

Schwarz H (1941) Othello der Maure von Venedig

Typescript Shakespeare-Bibliothek Munchen

Shei C-C and Pain H (2002) Computer-assisted teach-

ing of translation methods Literary and Linguistic


Steckel F (2012) Die Tragodie von Othello dem Mohren

von Venedig Frankfurt am Main Verlag der Autoren

Swaczynna W (1972) Die Tragodie von Othello dem

Mohren von Venedig Cologne Jussenhoven amp Fischer

Thiel S (2010) Understanding Shakespeare towards a visual

form for dramatic texts and language httpwwwunder-

standing-shakespearecom (accessed 16 January 2016)

Thiel S (2012) Othello map httpothellomapnandio


Thiel S (2014a) Visualizing translation variation http

transviss3-website-eu-west-1amazonawscom or www

tinyurlcomtransvis2014 (accessed 16 January 2016)

Thiel S (2014b) Visualizing Translation Variation

Designing Tools for Literary Scholars in Translation

Studies and Linguistics Masters Dissertation Bauhaus

University Weimar

Thiel S (2015) Macbeth Loglikelihoods httpmacbeth

s3-website-eu-west-1amazonawscomor wwwtinyurl

commacbthe (accessed 16 January 2016)

Toury G (2012) Descriptive Translation Studiesmdashand

Beyond Revised edition Amsterdam and

Philadelphia Benjamin

Venuti L (2004) Retranslations The Creation of Value

Bucknell Review 47(1) 25ndash38

Venuti L (2008) The Translatorrsquos Invisibility A History

of Translation Revised edition London and New York

Routledge

T Cheesman et al



Von Ledebur R (2002) Der Mythos vom deutschen

Shakespeare die Deutsche Shakespeare-Gesellschaft

zwischen Politik und Wissenschaft 1918-1945 Cologneand Weimar Bohlau

Wachsmann M (2005) William Shakespeare Die

Tragodie von Othello dem Mohr von Venedig BerlinGustav Kiepenheuer Buhnenvertriebs-Gmbh

Wang Q and Li D (2012) Looking for translatorsrsquo fin-

gerprints a corpus-based study on chinese translations

of ulysses Literary and Linguistic Computing 27(1)81ndash93

Wolff M J (1926) Shakespeares Werke ubertragen nach

Schlegel-Tieck Vol 14 Berlin Volksverband der

Bucherfreunde Wegweiser-Verlag

Zaimoglu F and Senkel G (2003)William ShakespeareOthello Bearbeitung Munster Monsenstein und

Vannerdat

Zeynek T (-1948) Shakespeare Othello Der Mohr vonVenedig Munich Ahn und Simrock Buhnen und

Musikverlag

Zimmer H (2007) Othello steht im Sturm Jugendstuck

frei nach Shakespeare Weinheim DeutscherTheaterverlag Weinheim

Notes1 lsquoVersion Variation Visualization Translation Array

Prototype 1rsquo at httpwwwdelightedbeautyorgvvvclosed Further project links wwwtinyurlcom

vvvex Alternative prototype tools were also built seeGeng et al 2011 2015 See further Cheesman 2015

2016 and Cheesman et al 20162 The existence of multilingual (re)translations can indicate

both popularity and prestige as in publishersrsquo blurbs fornovels lsquotranslated into X languagesrsquo For the Stanford

Literary Lab translations index popularity (Algee-

Hewitt et al 2016 p 3) But lsquomultiplersquo retranslationsoften also mean prestige some are included in institu-

tional curricula reviewed in lsquohigh-browrsquo media etc3 For example 1096 versions of the Bible in 781 lan-

guages at wwwbiblecom or approx 170 versions ofthe Quran in forty-seven languages at httpal-quran

info See Long (2007) and Hutchings (2015)4 Venuti (2004) focuses on retranslations which deliber-

ately challenge pre-existing translations Our corpus is

not so restricted5 See also Wang and Li (2012) digitally supported ana-

lysis of two Chinese translations of James Joycersquos

Ulysses

6 For details of the forty plus German texts used seewwwdelightedbeautyorg (lsquoGermanrsquo page)

7 lsquoIf virtue no delighted beauty lack Your son-in-lawis far more fair than blackrsquo (Othello 13287ndash8)Multilingual translations of this are crowd-sourcedby Cheesman at wwwdelightedbeautyorg

8 This remains less easy than we would wish Roos isworking with Eran Hadas on a more user-friendlycorpus-creation segmenting and aligning interfacein the course of a study of English translations ofthe Hebrew Haggadah from the C18 to now alsousing tools such as TRAViz (Janicke et al 2015)and Word2Dream (Hadas 2015) See Roos 2015and httpwwwtinyurlcomJewishDH

9 Cheesman collated MITrsquos lsquoMobyrsquo Shakespeare (httpshakespearemitedu) with Neillrsquos edition (2006) foradded dialogue and modern spellings We chose tosample Othello 13 partly because the English text isstable between editions at the level of speeches andspeech prefixes if not at the level of wording (exceptat 13275ndash6mdashsee Neill 2006 p 232) also for its var-iety of major character parts

10 httpwwwjuxtasoftwareorg Juxta helps map phyl-ogeny with the aim of (re)constructing an original oran authoritative edition We cannot study retransla-tions with any such aim There is no right translationThere may be a canonical translation but users feelfree to revise it because it is lsquojustrsquo a translation

11 The potential value of this interface to support ex-plorations of text-analytic features is illustrated by thelsquoMacbthersquo interface (Thiel 2015) users explore azoomable map of lsquoMacbethrsquo with a log likelihoodlemma table following the impetus of Hope andWitmore (2014) See also Thielrsquos (2010) earlier work

12 See Eder et al (2016) and stylometric translationsanalyses by Rybicki (2012) and Rybicki and Heydel(2013)

13 On the lsquofine line between retranslation and revisionrsquosee Paloposki and Koskinen 2010 There is no re-search on Wolff or indeed on most of the translatorshere

14 Cheesman named Eddy after (1) a formula he primi-tively devised as lsquo

PDrsquo adapting tfidf formulae (see

Cheesman and the VVV Project Team 2012 p 3) (2)his brother Eddy and (3) the idea that retranslationsare metaphorical lsquoeddiesrsquo in cultural historical flows

15 Formulae available A Euclidean distance BCheesmanrsquos original primitive formula C Viv asstandard deviation of Eddy D Dicersquos coefficient Eangular distance

16 lsquoA normalisation needs to be applied to compensatefor the effect of text length [so] we calculated




variation for a large number of base text segments ofvarying lengths then plotted average [Euclidean]Eddy value against segment length We found a loga-rithmic relationship between the two and arrived at anormalisation function that gives an acceptably con-sistent average Eddy value regardless of text lengthrsquo(Flanagan in Cheesman et al 2012ndash13) Eddy for-mula E (angular distance) appears to address thelength normalization problem to some extent

17 Stephen Ramsay commented on the lsquograceful andilluminatingrsquo interface that lsquoprompts various kindsof lsquolsquonoticingrsquorsquo and encourages an essentially playfuland exploratory approach to the lsquolsquodatarsquorsquorsquo (personalcorrespondence 26 May 2014)

18 Neill glosses lsquovirtuersquo as lsquomoral excellencersquo lsquomanlystrength and couragersquo and lsquoinherent naturersquo at13287 lsquopower strength of characterrsquo at 13315(Neill 2006 p 233 and 235mdashsee there also for lsquofigrsquo)

19 Roos (2015) uses Eddy and Viv to explore bowdler-ization in English Haggadah texts

20 Zeynek died in 1948 his translations are undated21 Stylometry and common sense recommended nar-

rowing the corpus to give less lsquonoisyrsquo results Iexcluded prose study versions adaptations with ex-tensive omissions contractions expansions and add-itions C18 and C19 versions including all versions ofBaudissin (1832) leaving fifteen versions Gundolf(1909) Schwarz (1941) Zeynek (-1948) Flatter(1952) Rothe (1956) Schaller (1959) Schroder(1962) Fried (1972) Swaczynna (1972) Laube(1978) Rudiger (1983) Motschach (1992) Gunther(1995) Buhss (1996) Wachsmann (2005)

22 The norm in German Shakespeare translation is thatformal variation in the original (prose blank verserhymed verse or another metrical scheme) should bereplicated or analogously marked Roos (2015) reportssimilar findings for the Haggadah rhyming verse sec-tions have higher Viv if translators use rhyme

23 We thank a DSH referee for pointing out this

possibility24 Roos (2015) similarly finds lower Viv value in Bible

quotations (the most canonical segments) in

Haggadah translations25 Based on the two-line verse segments found manu-

ally the length range was set at 60ndash100 characters

Iagorsquos lengthy prose speeches include more examples

than were segmented and aligned26 Baudissin (five versions 1855ndash2000) was added to the

corpus previously used to recognize this translationrsquos

enduring relevance27 See Neill 2006 p 231 The MIT text (from an 1860s

edition) is quoted but with Neillrsquos line-numbering28 We also envisage training applications An interface

enabling trainee translators and trainers to compare

versions would have great practical value as an ad-

junct to a computer-assisted translation system and

or an assessment and feedback system29 Shakespeare retranslations are found at scattered sites

Larger curated corpora are accessible in Czech and

Russian c400 aligned texts (twenty-two versions of

Hamlet) at httpwwwphilmuniczkapradi c200

texts (twelve versions of Hamlet) at httprus-shake

rutranslations30 The term lsquosurrogatersquo is taken from Mueller (2003ndash14)

Ideally our system would include page images31 Roos is working on this with Eran Hadas32 Difficulties include in-text variants (eg in critical

editions or translatorsrsquo directorsrsquo and actorsrsquo

copies) and orthographic variations (archaic and vari-

ously modernized forms ad hoc forms fitting met-

rical rules other non-standard forms) Rather than

standardize texts to facilitate comparisons the ma-

chine should learn to recognize underlying

equivalences

T Cheesman et al



German versions of a work by Shakespeare Initial findings lead to more ques-tions than answers

1 Introduction

Our project began with a simple observation and anintuition The observation in any set of multipletranslations in a given language variation amongthem varies through the course of the text Sometext units or chunks (at any level from word sayup to chapter or character part in a play) are morevariously translated than others The intuition thisvariation can be used to project an annotation ontothe translated text indicating where and how theextent of translation variation varies This is the es-sence of our online system It uses a lsquoTranslationArrayrsquo (a parallel multi-translation corpus alignedto a lsquobase textrsquo of the translated work) to achievelsquoVersion Variation Visualizationrsquo Here lsquoversionrsquoencompasses any text which can be at least partlyaligned with others But the website strapline islsquoExplore great works with their world-widetranslationsrsquo1

If multiple translations of a work exist then thework is enduringly popular andor prestigious ca-nonical or classic in the translating culture typicallylsquogreat worksrsquo of scripture literature philosophyetc2 Interest in comparing such worksrsquo multipletranslations is surprisingly limited Some largealigned retranslations corpora are publicly accessibleonline (works of scripture)3 but user access is lim-ited to two parallel texts and no analytic tools areprovided No similar resources exist for any secularworks at all yet This reflects the notorious lsquoinvisi-bilityrsquo of translators and translations in general(Venuti 2008) A key aim of our project is tomake them visible

Retranslations are successive translations of thelsquosamersquo source work often somehow dependent onprecursor (re)translations The source works con-cerned are mostly unstable texts in their originallanguage what translators translate varies andchanges And so does how they do it The gamutruns from word-for-word renderings to very freeadaptations or rewritings with little obvious relationto the source Relay translationmdashvia a third

languagemdashintroduces further variation If transla-tions are reprinted or otherwise re-used they tendto be changed again Venuti (2004) argues that re-translations (more than most translations) lsquocreatevaluersquo in the target culture4 A first translation of aforeign work creates awareness of it If retranslationsfollow the work becomes assimilated to the targetculture If retranslations multiply each both re-inforces the value and status of the work in thetarget culture and extends the range of competinginterpretations surrounding it Retranslations there-fore throw up questions going well beyond linguisticand cultural transfer concerning lsquothe values and in-stitutions of the translating culturersquo and how theseare defended challenged or changed (Venuti 2004p 106)

Within Translation Studies lsquoretranslation stu-diesrsquo is underdeveloped despite its fundamental im-portance for translation linguistics andcommunication as well as comparative trans-national cultural studies As Munday (2012)argues retranslations are important resources be-cause no single utterance or text exists in isolationfrom alternative forms it might have taken Anyextant text is surrounded by a lsquopenumbrarsquo of lsquoun-selected formsrsquo (Munday 2012 p 13 citing Grant2007 pp 183ndash4) so any translation is surroundedby lsquoshadow translationsrsquo (Johannson 2011 p 3citing Matthiessen 2001 p 83) Sets of translationsby different translators (or the same translators atdifferent moments) make visible at least someotherwise unselected forms This offers scope forstudying lsquothe value orientations that underlie theseselectionsrsquo (Munday 2012 p 13) Our project seeksto go even further from the how and why of vari-ation among translations back to the varying cap-acity of the translated text to provoke variation

The article is organized as follows Section 2 re-views related work including statistical studies intranslation variation Section 3 presents our soft-ware project covering our Aligner CorpusOverviews (including stylometric analysis) andour key innovation an interface deploying lsquoEddy

T Cheesman et al




2 Related Work





















T Cheesman et al





















T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al




2 Related Work





















T Cheesman et al





















T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al










T Cheesman et al





















T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al





















T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al



Fig

1

Ali

gnm

ent

map

so

fth

irty

-fiv

eG

erm

anO

thel

lo1

3(1

766ndash

2010

)




321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al



321 Alignment maps








T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al

















aj frac14 Ui


T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al





jSj


Eddy frac14


jZi Aij2

vuut


Eddy frac142cos1 AZ

IAIIZ I












Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al



Tab

le1

lsquoVir

tue

Afi

grsquo

inth

irty

-tw

oG

erm

antr

ansl

atio

ns

(176

6ndash20

12)

Nu

mb

ers

lsquoEd

dyrsquo

ran

k

Len

gth

ran

k

Tra

nsl

atio

ns

Bac

k-t

ran

slat

ion

sS

ou

rces

Inte

rtex

ts

1T

uge

nd

P

fiff

erli

ng

Vir

tue

[No

tw

ort

ha]

chan

tere

lle

Wie

lan

d17

66(S

)(P

)

2H

Tu

gen

dmdash

Den

Hen

ker

auch

V

irtu

emdash

[To

Hel

lw

ith

]th

eex

ecu

tio

ner

too

E

sch

enb

urg

(ed

E

cker

t)17

79(S

)

3L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Sch

ille

ran

dV

oss

1805

(P)

Cf

4

11

4L

Tu

gen

d

Nar

ren

spo

ssen

V

irtu

eF

oo

lsrsquo

bu

ffo

on

ery

Ben

da

1826

Ort

lep

p18

39

5L

Tu

gen

d

Ab

gesc

hm

ackt

V

irtu

eV

ulg

ar

B

aud

issi

n[S

chle

gel-

Tie

ck]

1832

(P)

6T

uge

nd

Z

um

Hen

ker

Vir

tue

To

the

exec

uti

on

er

[frac14b

ed

amn

ed]

Bo

den

sted

t18

67

7T

uge

nd

L

eere

sG

efas

el

Vir

tue

Min

dle

ssd

rive

lJo

rdan

1867

8T

uge

nd

W

isch

iwas

chi

Vir

tue

Dri

vel

Gil

dem

eist

er18

71

9L

LT

uge

nd

A

eh

Vir

tue

Ugh

V

isch

er18

87

10T

uge

nd

P

feif

dra

uf

Vir

tue

Wh

istl

eo

nit

[frac14

Do

nrsquot

give

a

dam

nfo

rit

]

Gu

nd

olf

1909

11L

LT

uge

nd

P

oss

en

Vir

tue

Bu

ffo

on

ery

Bau

dis

sin

(ed

W

olf

f)19

26

12L

Tu

gen

d

Du

mm

hei

tV

irtu

eSt

up

idit

yE

nge

l19

39(T

)

13E

ner

gie

Ein

Sch

mar

ren

E

ner

gy

No

nse

nse

[d

iale

ctal

S

Ger

man

]Sc

hw

arz

1941

(T)

Cf

23

14L

Tu

gen

d

Ach

was

V

irtu

eO

hco

me

on

B

aud

issi

n(e

d

Bru

nn

er)

1947

(S)

15H

HN

ich

td

ieK

raft

Z

um

lach

en

No

tth

est

ren

gth

L

augh

able

Z

eyn

ek-

1948

(T)

16L

lsquoTu

gen

drsquo

Qu

atsc

h

lsquoVir

tuersquo

N

on

sen

se

Fla

tter

1952

17T

uge

nd

W

eiszlig

eM

ause

V

irtu

eW

hit

em

ice

Ro

the

1956

18M

ach

tD

um

mes

Zeu

gP

ow

er

Stu

ffan

dn

on

sen

se

Sch

alle

r19

59

19T

uge

nd

K

ein

eF

eige

wer

tV

irtu

eN

ot

wo

rth

afi

gSc

hro

der

1962

20T

uge

nd

fi

ckd

rau

fV

irtu

efu

ckit

Swac

zyn

na

1972

(T)

21H

HIn

dei

ner

Mac

ht

Ach

was

In

you

rp

ow

er

Oh

com

eo

n

F

ried

1972

(P)

Cf

23

27

22T

uge

nd

E

inQ

uar

kV

irtu

eQ

uar

k[s

oft

chee

sen

on

sen

se]

Lau

terb

ach

1973

(T)

Cf

27

23M

ach

tSc

hm

arre

n

Po

wer

N

on

sen

se

[dia

lect

al

SG

erm

an]

E

ngl

er19

76(S

)

24H

HN

ich

tin

dei

ner

Mac

ht

Son

Qu

atsc

h

No

tin

you

rp

ow

er

Wh

atn

on

sen

se

Lau

be

1978

(T)

Cf

27

25T

uge

nd

E

inD

reck

V

irtu

eF

ilth

[C

rap

]R

ud

iger

1983

(T)

26L

LT

uge

nd

Q

uat

sch

Vir

tue

No

nse

nse

B

olt

ean

dH

amb

lock

1985

(S)

27H

HN

ich

tin

dei

ner

Mac

ht

Qu

ark

No

tin

you

rp

ow

er

Qu

ark

G

un

ther

1995

(P)

Cf

31

32

28H

Da

kan

nst

du

lan

geb

eten

Yo

uca

np

ray

alo

ng

tim

e[frac14

No

tu

nti

lth

e

cow

sco

me

ho

me]

Mo

tsch

ach

1992

(T)

29L

Aff

enkr

amA

pe-

rub

bis

h[frac14

Cra

p]

Bu

hss

1996

(T)

30H

HC

har

akte

rA

mA

rsch

der

Ch

arak

ter

Ch

arac

ter

Ch

arac

ter

my

arse

Zai

mo

glu

and

Sen

kel

2003

31H

HN

ich

tin

dei

ner

Mac

ht

Qu

atsc

h

No

tin

you

rp

ow

er

No

nse

nse

L

eon

ard

2010

(T)

32N

ich

tin

dei

ner

Mac

ht

No

tin

you

rp

ow

er

St

ecke

l20

12

Han

dL

ind

icat

eh

igh

est

(H)

and

low

est

(L)

seve

nE

dd

yva

lue

ran

kin

gsan

dle

ngt

hra

nki

ngs

Alt

ern

ativ

etr

ansl

atio

ns

tolsquoT

uge

nd

rsquofrac14

lsquovir

tuersquo

are

un

der

sco

red

Sou

rces

frac14

no

win

pri

nt

(S)frac14

stu

dy

text

(T

)frac14

no

bo

ok

trad

ed

istr

ibu

tio

n(t

hea

tre

text

)

Inte

rtex

ts

(P)frac14

pre

stig

iou

sin

flu

enti

al

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al



























T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al



Tab

le2

lsquoViv

valu

esrsquo

intw

oli

ner

sin

Oth

ello

13

gen

erat

edb

ytw

enty

Ger

man

vers

ion

s

(continued)









Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al








Tab

le2

Co

nti

nu

ed

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al


















Funding















January 2016)









Vol 8 Berlin Reimer




Leipzig Brockhaus










46(2) 207ndash20














January 2016)

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al


















Felix Bloch Erben











Verlag Desch












Macmillan


1 Berlin Bondi 1920



Taschenbuch Verlag



January 2016)





































































Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al




















Munich Drei Masken




January 2016)


















4 Baden-Baden Holle








pp 231ndash48




28(4) 708ndash17


Legacy Munster LIT


Rutten amp Loening























University Weimar











Routledge

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al















Vannerdat


Musikverlag
















Ulysses


















































equivalences

T Cheesman et al




































equivalences

T Cheesman et al



multi-retranslation corpora: visibility, variation, value

Documents