socy3700 selected overheads for the final exam prof. backman spring 2008

SOCY3700 Selected Overheads for

the Final Exam

Prof. BackmanSpring 2008

Stages in Field Research

• Choosing the site– Start where you are

• Getting in– Being accepted– Anonymity

• Getting on– With self, “the folk”, conscience and

colleagues• Gathering data

– Logging– Interviews

• Focusing• Analysis• Write up

• (Adapted from Lofland and Lofland)

Street Corner Society: The Social Structure of

an Italian Slum

William Foote Whyte, 1943 (third edition, 1981)

Whyte Bio

• Educated middle class upbringing• Loved to write• Attended Swarthmore in suburban

Philadelphia• Engaged in some reform activities

in college, but engaged even more in writing

• Wrote a novel, decided it was lousy because he didn’t have enough to say

• Got a Junior Fellowship at Harvard – three years just to hang around and do whatever research took his fancy (sort of)

The Research Problem• Whyte came to Harvard knowing

mainly that he wanted to study slums and somehow improve the world

• Social scientific literature was just beginning to appear. He read lots of it

• Other folks at Harvard had done similar work and were developing some theoretical ideas about group process– One would not think one would go to a

slum to study group process, but in the end that was a big part of what Whyte did

• Many of the ideas Whyte when he started his work came to naught– “We set out on the frontiers of our

personal knowledge and began exploring beyond those frontiers” (Whyte 1984:63)

“Cornerville”

• In the usual fashion, Whyte gave his city and neighborhood a psuedonym. Cornerville refers to the slum, now known to be Boston’s North End. He called Boston “Eastern City.”

• At the time (around 1937) Cornerville was suffering the effects of The Great Depression

• Predominately Italian in a city whose big politicians were mostly Irish

• Many residents spoke only Italian

Getting In• Wandered around Boston,

settled on Cornerville because it “looked like” his vision of a slum

• Could observe from the outside, but wanted to observe from the inside

• After various failed schemes, introduced to Doc by the social worker in charge of girls’ programs at the local settlement house

• Moved into the neighborhood

Doc

• Doc (a psuedonym for Ernest Pecci) is probably the most famous informant in sociology– A pretty good sociologist himself

for someone who never had a sociology course

• Late 20s, mostly unemployed guy from the neighborhood

• Informal leader of a group of similarly underemployed age mates

• Interested in making things better

Doc and Bill

• Doc’s famous response to Whyte’s first rambling description of what Whyte was trying to do in Cornerville: “Do you want to see the high life or the low life?”

• Doc served as Whyte’s sponsor, guide, and “member validator”– Having a sponsor can be a problem in

settings with a great deal of conflict, as you may be seen as being on your sponsor’s side

– “Member validator”: insider who reviews the sociologist’s analysis from an insider’s point of view

Getting On

• Whyte moved into Cornerville, taking a room with a family

• Whyte tried to learn Italian– Though never got proficient, he

felt his efforts gave him a great deal of credibility, especially with the older generation

• Joined various clubs, becoming secretary of at least one

• Hung out with Doc’s gang• Returned regularly to Harvard

for baths and brainstorming with other social scientists

Going Native• When you start to act like and

especially to think like the people you are studying, you have gone native– Quite common occurrence– It is difficult to completely go native

• Whyte’s efforts to swear like the other guys weren’t successful, partly because they wanted him to be himself

– Can get you in trouble• Whyte voted illegally• Whyte almost inadvertently got

engaged because he didn’t understand as much of native practice as he thought

– The natives aren’t always grateful

Street Corner Society: Sources

Whyte, William F. [1943] 1981. Street Corner Society. 3rd ed. Chicago, IL: University of Chicago Press.

Whyte, William F. 1984. Learning From the Field: A Guide from Experience. Newbury Park, CA: Sage.

Whyte, William F. nd. Various personal and classroom communications.

Bernard on Unstructured Interviews

• H. Russell Bernard – cultural anthropologist from U of Florida, author of a research methods text I have used in advanced research methods courses– As surveys are to sociologists, so

unstructured (and semi-structured) interviews are to cultural anthropologists

– As a researcher, journal editor, and methods text author, Bernard has been given credit for strengthening the rigor of anthropological research

Source: Bernard, H. Russell. 1995. Research Methods in Anthropology: Qualitative and Quantitative Approaches. 2nd ed. Walnut Creek, CA: AltaMira. Mostly Chapter 10, pp. 208-36.

Bernard on Unstructured Interviews (2):

Continuum of Interview Situations

Since the researcher is an outsider, the locals will generally be aware that any contact is likely to involve information gathering

• Continuum of situations based on how much the interviewer controls the situation

1. Informal interview – more or less normal conversation

- Typical early in research- Useful for rapport- Useful later for finding topics that might

have been overlooked


Continuum of Interview Situations (2)

2. Unstructured interview – not just normal conversation, but with minimal control over the responses of the interviewee

3. Semi-structured – like unstructured but with an interview guide

- Interview guide: written list of topics, probes, etc. intended to be covered in the interview

- More formal than unstructured

4. Structured – questions (and often answer choices) established ahead of time by the interviewer

- For example, standard survey interviews, self-administered questionnaires


Starting the Interview

• Assure anonymity

• Explain their importance to your understanding

• Ask for permission to record the interview and to take notes– The value of the interview much

lower if you can’t record or take notes

– Even with recorder it helps to take occasional notes


Let the Informant Lead

Rule # 1: get an informant on the topic and get out of the way– You pick the topic, interviewee

provides the content– In general, it is the interviewee’s

ideas you are interested in, not yours

• This rule is not always slavishly followed– Interviewee may stray off topic– You may have ideas you want

responded to


Probes

• Use probes to guide interview• Probe (Bernard definition):

stimulating an informant to give more information without injecting yourself so much into the interaction that you get only a reflection of yourself in the data– There are many types of probes– Our textbook definition: a neutral

request to clarify an ambiguous answer, to complete an incomplete answer, or to obtain a relevant response (p. 192 in Neuman 2007)


Types of Probes 1

• Silent probe – don’t say anything when the interviewee stops– Difficult to do appropriately– Culturally sensitive since

different cultures have different rules about silence

• Echo probe – repeat the last thing the interviewee said– Signals that you are interested in

what was said without saying why or suggesting what to say


Types of Probes 2

• Uh-huh (neutral) probe – make regular affirmative noises, as one often does in normal conversation to indicate you are still listening and are interested– Keeps the interviewee talking

Rule #2: In general, more talking by the respondent is better– Hence, longer responses are

better


Types of Probes 3

• The long question probe – instead of keeping a question short and to the point, asking a long roundabout question– You’re modeling the kind of long

answer you want to get back– The trick is not to guide the

answer as you ask the question


Types of Probes 4

• Probe by leading – ask a leading question as a way of focusing provoking the interviewee– Usually we try not to lead, but

sometimes respondents seem to be avoiding a topic or conclusion

– Can be used to ask about more specific incidents or about what happens when things don’t work out as expected

– Often based on earlier interviews


Types of Probes 5

• Phased assertion (baiting) probe – you take some information that may or may not be true and ask questions as if it were true– For example, “I guess Hilary and

Barak are friends again. I wonder why.”

– This is a favorite ploy of gossip-mongers


Verbal Respondents; Equipment

• Verbal respondents – don’t be afraid to interrupt a long winded respondent who is wandering away from your topic. Try to be graceful about it

• Equipment – always make sure that your tape recorder is ready before the interview (fresh tapes and batteries)


Uses of Unstructured Interviews

• A primary source of raw data• Preparation for semi-structured

interviews• To get info from people unlikely

to give more formal interviews• Developing rapport• Studying sensitive topics

– E.g., hot political topics, sexuality, racial prejudice

– Conflict: you can get wide range of information from multiple interviewees

Bivariate Relationships with

Integer-level Variables

Preliminaries to multiple regression

Steps in Analysis of Bivariate Relationships

Between Integer-level Variables

• Look at scatterplot– Dependent variable as the Y

(vertical) axis– Independent variable as the X

(horizontal) axis

• Make best-fit line– Since it is a line, we call it linear

regression– Since we have only one

independent variable, we call it simple linear regression

• Calculate slope (b)• Calculate goodness of fit (r)

Interpretation of Simple Regression Results

Equation: Dependent

= intercept + coefficient * independent + error

• Coefficient (aka b, beta, or regression coefficient) tells how many units of the dependent variable go with the increase of one unit on the independent variable– Mathematically, the slope

Interpretation of Simple Regression Results (2)

• Correlation coefficient (aka r, Pearson’s r) – a measure of how well the line fits the data, usually interpreted as how strong the relationship is– Measures the “goodness of fit”

• The higher the absolute value of r, the better the fit

– Ranges between -1 and 1• Positive coefficient means there is a

positive relationship between the two variables (high on the independent goes with high on the dependent)

• Negative coefficient means there is a negative relationship between the two variables (high on the independent goes with low on the dependent)


• Intercept – how many units of the dependent variable you would be expected to have with 0 units of the independent– Mathematically, it is where the

line crosses the vertical axis

• Error – the difference between what was actually measured for the dependent variable for a particular case and the measurement predicted by the equation for the line


• Statistical significance – tests how sure we are that the regression coefficient is not zero OR that the correlation coefficient is not zero– Conventionally we use the 95

percent confidence level– At the 95 percent confidence

level, the probability of a false positive is less than 5 percent, usually written as p<.05


ExampleDependent variable: violent crimes per

100,000 populationIndependent variable: percent of population

15 and up who are currently divorcedCorrelation coefficient = 0.24

There is a positive relationshipRegression coefficient = 38.6

For every additional 1 percent to the percent divorced of the population 15+ there is an increase in the violent crime rate of 39

Intercept = 160If no one in the population were divorced, there would be 160 violent crimes per 100,000

The relationship is significant at the p<.048 level

Multiple Regression

• Multiple regression is multiple because it allows the use of more than one independent variable– This is nice since so much of

social life has multiple causes

• Multiple regression is probably the most important statistical tool in use in sociology today

• There are many similarities between simple regression and multiple regression

Multiple Regression (2):

Similarities with Simple Regression

• The key mathematical operation is fitting a line to the data points– The method is the same: choose the

line that minimizes the squared distances between the points and the line

• Called the method of least squares; the line is sometimes called the least squares line. Sometimes it is called the ordinary least squares (OLS) line

• There is a statistic for the overall fit of the line to the data points

• Each independent variable gets its own regression coefficient


Differences from Simple Regression

• Scatterplots are in hyperspace– That is, for each variable, including the

dependent, there is another dimension in the graph

• They’re really hard to draw!

• The goodness of fit statistic doesn’t tell you the direction of the relationships– We use R (not r) as its symbol– Actually, we usually use R2

– R2 tells us the proportion of variation in the dependent variable that is accounted for by the independent variables


Interpretation of Regression Coefficients

• New term: ceteris paribus – all other things being equal

• A regression coefficient tells us how much change in the dependent variable is associated with a change of one unit in the coefficient’s independent variable, ceteris paribus


The Regression Equation

• Multiple regression is based on the matrix equation

Y = XB + e

where Y is the dependent variable, X is the matrix of dependent variables, B is a vector of regression coefficients (and the intercept), and e is the error


Varieties of Multiple Regression

• Ordinary regression makes certain assumptions about the relations between the independent variables and about the errors– These assumptions are not always

met

• Ordinary regression is limited to only one dependent variable

• There are a large number of modifications to ordinary regression that overcome some of its limitations and to loosen the assumptions


The General Linear Model

• The collection of modifications and extensions to ordinary regression is called the general linear model– The GLM is based on the equation

given earlier– It brings together a wide range of

statistical methods, some of which had been invented independently

• The GLM is a conceptual and methodological breakthrough paralleled in its importance for quantitative social science only by the discovery of sampling theory

socy3700 selected overheads for the final exam prof. backman spring 2008

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