emotional segues and the management of emotion by women and men

Emotional Segues and the Management of Emotion by Women and MenAuthor(s): Kathryn LivelySource: Social Forces, Vol. 87, No. 2 (Dec., 2008), pp. 911-936Published by: Oxford University PressStable URL: http://www.jstor.org/stable/20430896 .

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Emotional Segues and the Management of Emotion by Women and Men

Kathryn Lively, Dartmouth College

Recent studies suggest that gender may be less influential on the experience of emotion than originally believed. Most ofthese studies, however, havefocused almost exclusively on gender differences in discrete emotional experiences, paying less attention to the ways in which emotions may co-occur within a relatively short period. Using the General Surveys 1996 emotions module, I examine the correlational structure of nine latent emotionfactors - tranquility, joy, hope, pride, self-reproach, anger, rage, fear and distress - by gender. Using the technique ofshortestpath analysis, Ifind womens most common emotionalpathways are longer, more complex, and more likely to use more positive and less powerful emotions than those most common to men. Implicationsfor emotion management, both personal and interpersonal, are discussed.

Sociologists and laypersons generally have agreed that women and men occupy different emotional spheres (Cancian 1987; Hochschild 1983). Cultural arguments regarding gender and emotion suggest that women and men are socialized to experience particular emotions and, at the same time, avoid the experience of others. Anger, for example, is typically deemed more appropriate for men, whereas sadness seems more fitting for women (Stearns and Stearns 1986). More generally, early sociological research suggests that women are more likely than men to report experiencing emotions that can be thought of as relatively weak such as contentment, depression and anxiety, and less likely to experience and express emotions that are viewed as relatively strong such as pride, anger and rage (Stearns and Stearns 1986).1 Women are also more likely to be expected to feel and express relatively positive emotions, such as happiness or joy (Hochschild 1979, 1983).

In contrast, more recent studies of gender and emotion, particularly those using survey data and experiments, suggest that the effects of gender may be overstated or have winnowed through the years (Heise

I would like to thank Denise Anthony, David Heise, Melissa Herman, Deborah King, Brian Powell, Abigail Sewell and Michael Yacavone for their insightful comments on earlier drafts of this manuscript. I am especially grateful to the anonymous reviewers for their assistance, as well as the editors of Social Forces. This project was generouslyfunded by the Nelson Rockefeller Centerfor Public Policy at Dartmouth College. Direct correspondence to Kathryn Lively, Dartmouth College, 103 Silsby Hall, Hanover, NH 03755. E-mail: [email protected]. ? The University of North Carolina Press Social Forces 87(2), December 2008



912 . Social Forces 87(2)

2007; Lively and Powell 2006; Simon and Nath 2004). Indeed, in one of the most comprehensive studies of gender and emotion to date, Simon and Nath report few differences in the overall frequency with which men and women experience specific emotions. In a similarly extensive review of the small group literature, Ridgeway and Smith-Lovin (1999) conclude that gendered differences in emotions during interactions could be attributed, in most cases, to institutional patterns of status and power. One reason why recent accounts of gender and emotion may yield

fewer significant results than expected may be that these investigations deal almost exclusively with discrete emotional outcomes, such as the likelihood of experiencing or expressing particular emotions (Lively and Powell 2006; Simon and Nath 2004). While these studies have increased our understanding of how single outcomes are distributed, they may have inadvertently diverted attention away from other important gendered aspects of emotion, including the complexity of women's and men's emotional lives that includes experiencing multiple emotions simultaneously or in rapid succession (Smith-Lovin 2002).

Lively and Heise (2004) argue that the correlational structure of emotions indicates the process of emotion management. Correlations between disparate emotions represent the relative nearness or accessibility from one emotion to another. They suggest that these "emotional segues" (or "shortest paths") may reveal how actors traverse multiple emotions to achieve specific emotional outcomes. They also present limited evidence that the correlations between particular emotions may differ by gender, but they do not determine explicitly whether and how the process of emotion management may differ for women and men.

Does the correlational structure of emotional experience differ for women and men? And, if so, do these differences suggest variation in the ways in which women and men manage their emotions?

Background

Emotion Management

One of the more compelling ideas that sociologists bring to the study of emotion is the degree to which emotion is inherently social and subject to acts of management (Hochschild 1983). As Hochschild so astutely noted, individuals who experience their emotions as normatively inappropriate (due to either their immediate situation [1975] or their place within the larger social structure [1979]) often engage in emotion management in order to bring their emotions in line with pre-existing feeling norms. In her initial descriptions of emotion management, Hochschild observed that individuals who wanted to change their emotions to better adhere to feeling rules often drew on deeply held emotion memories or engaged in "deep acting."(1983:49)



Emotional Segues . 913

Since feeling rules are mostly gendered, women may be more likely to manage their experiences of anger or rage by remembering times marked by positive and less potent feelings such as happiness or compassion. Similarly, men may be more likely to transform their experience of depression or fear by drawing on memories involving more negative or powerful emotions, such as self-reproach or anger. Although most discussions of emotion management focus on converting negative emotions into positive ones, emotion management also refers to the opposite transformation (Hochschild 1983; Sutton 1991).

As scholars attempted to clarify how emotion management occurs, it became apparent that some emotional transformations may be more difficult than others. In fact, some emotional transformations seem to require transitioning through multiple emotions in order to be successful. In her analyses of political speeches, Wasielewski (1985) showed how charismatic leaders attempted to move their audiences through particular streams of emotion in order to achieve their political goals. Britt and Heise (2000) also found that social movement organizations, at least those with socially marginalized constituents, had to first instill fear and anger before they could engender pride. They argued that individuals whose identities are marked predominantly by feelings of shame (which they classed as a negative, weak and inactive emotion) are less likely to demand equal treatment compared to those whose identities were marked predominantly by feelings of pride (which is a much more positive, potent and active emotion). Outside of the political realm, Thoits (1996) and Francis (1997) also revealed how therapists used stylized techniques to lead individuals from one emotion state to another in order to achieve their emotional goals. Despite the gendered nature of appropriate feelings, researchers mostly have not determined whether emotional transformations - particularly those that require transitioning between multiple emotions - differ for women and men.2

Emotional Segueing

In an attempt to determine how individuals transition through intervening emotions in order to achieve specific emotional outcomes, Lively and Heise (2004) used structural equation modeling to introduce the idea of emotional segueing. Using data from the 1996 General Social Survey's emotion module, they examined the correlational structure of nine latent emotion factors: tranquility, hope, joy, pride, self-reproach, anger, rage, fear and distress, arguing that emotions that co-occur frequently within a seven-day period may be relatively accessible to one another, while those that co-occur infrequently (or not at all) may be less accessible.34 To further explore this idea, they applied shortest-path analyses (Rosen




1988:401-10) to the correlations among these factors, and constructed a remoteness index of emotional states that yielded shortest paths between any two emotions. The remoteness score between two emotions, they argued, provides a quantifiable representation of how much emotion management it takes to move from one emotional state to another. These shortest paths are consistent with emotional transformations documented previously in studies of social support groups (Francis 1997; Thoits 1996), social movement organizations (Britt and Heise 2000), political speeches (Wasielewski 1985) and total institutions (Goffman 1961).

Emotional Segueing: How and Why?

The shortest paths noted by Lively and Heise (2004) use the fundamental dimensions of meaning first identified by Osgood, May and Miron (1975) and serve as the basis for Affect Control Theory (Heise 1979). Affect Control Theory disaggregates emotions (along with other elements of a social interaction - e.g., social actors, social objects, behaviors, settings and attributes) into three fundamental dimensions: Evaluation (how good or bad something is), Potency (how powerful or weak something is), and Activation (how lively or quiet something is). Simply put, emotions that have similar EPA profiles are more similar than those that have dissimilar EPA profiles. EPA profiles are represented by a series of three values that each range from -4.3 to 4.3 (Heise 2007). Evaluation is represented by the first value, Potency the second, and Activation the third. For example, the combined male-female EPA value for rage is -1.65, .38, 1.81. Rage, thus, is considered to be a fairly negat/ve, slightlypowerfu/ and fairly active emotion.

An examination of the emotional segues originally introduced by Lively and Heise (2004) reveal that shortcuts between positive and negative emotions (or emotions that mark the poles of the Evaluation dimension) tend to occur in concert with changes in Potency and Activation. That is, shortest paths between positive and negative emotions are marked by emotions that are similar in term of Potency and or Activation. For example, Lively and Heise report that the shortest path between tranquility and anger occurs via pride. The average EPA profile of the tranquility factor (which includes the single item indicators happiness, contentment, at ease and calm) is 2.33, 1.56, 1.01. The average EPA profile for the anger factor (which includes angry and mad [at]) is -1.50, -.25, .98. The EPA profile for pride is 2.27, 2.22, 1.70.5 The shortest path between tranquility and anger appears to occur when individuals also experience a change in Potency in addition to the more apparent change in Evaluation. As seen in Figure 1, the shortest pathway from tranquility (again, 2.33, 1.56, 1.01) to rage (-1.65, .38, 1.81), uses joy (2.84, 2.08, 1.84). It is the similarity of rage and joy (in terms of their levels of Activation, marked in bold)




Figure 1. Shortest Path Between Tranquility and Rage

/ Shortest Path: 16 \

Tranquility Rage EPA: 2.33, 1.56,1.01 EPA: -1.65, 0.38, 1.81

Shortest Path: 5 Shortest Path: 7

Joy EPA: 2.84, 2.08, 1.84

Shortest Path (Via Joy): 12

Note: derived from Lively and Heise 2004

that makes them relatively accessible to one another; however it is the relative similarity of joy and tranquility (in terms of their levels of Potency and Evaluation, both marked in italics) that completes the path. Thus, one can envision emotion management occurring along pathways marked by similar dimensions of affective meaning.

Gender Differences in Emotional Segueing

Given that some emotions are viewed as more appropriate and therefore more likely to occur for women than for men (Hochschild 1979), are there significant gender differences in the shortest paths between emotions? Lively and Heise (2004) did not explicitly explore gender differences in the shortest paths between specific emotions; however, they did present evidence illustrating significant differences in women's and men's experiences of emotion when examining the correlations between the




original 19 individual emotion states investigated within the GSS. They reported 29 significant gender differences in correlations, which is approximately four times more than would be expected by chance.

Although the most dramatic disparities occurred between positive and negative emotions, Lively and Heise's results showed that gender differences in correlations also occurred between similarly valenced emotions, with women's emotions significantly more dispersed than men's. They also reported that women tend to experience their positive emotions as significantly more positive and their negative emotions as significantly more negative than do men. Taken together, these findings demonstrate subtle differences in the relationships between specific emotions; however, they convey but a preliminary understanding of gender's relationship to everyday emotion - particularly to emotional transformations and one's ability to segue between one emotion and the next. Despite the suggestive nature of their findings, Lively and Heise's analyses do not determine whether these correlational differences result in different shortest paths for women and men. Although sociological studies document women's greater tendency

to engage in emotion management than men in similar situations, few actually document gender differences in the emotional transformations that occur during these processes. One exception, albeit implied only, is Hochschild's (1989) ethnographic account of the "second shift." Here, she demonstrates that husbands and wives managed their anger and resentment over perceived inequities in the division of household labor by making strategic comparisons that protected the self and obscured blatant disparities. Although not focused on emotional transformations, per se, her results suggest that there are gender differences in coping strategies, as well as in the emotions that accompany them.

Implicit within Hochschild's (1989) analysis is that the coping strategies of wives led them to experience a range of emotions - distress, anger and fear - prior to experiencing more positive emotions regarding their situations, including pride at being able to handle the demands of work and family and joy at being true to their gender convictions. The strategies used by husbands, however, allowed them to transform their negative feelings relatively quickly and easily. Some husbands compared themselves directly to men who did less around the house than they themselves did, enabling them to transform their anger at being asked to contribute more or their self-reproach at having not done enough into feelings of pride. Other husbands simply defined the struggle between work and family as their wives' issue, or absented themselves from the situation entirely by retreating to a workshop or to the workplace. These types of strategies allowed them change their negative emotions into more sanguine feelings such as tranquility. Granted, Hochschild's (1989)




analysis is one highly contextualized example. However, these findings are not inconsistent with qualitative studies of the workplace illustrating men's greater tendency to distance themselves from the emotional demands of others (see Lively 2006 for a recent review).

Expectations

The aforementioned literature suggests two competing sets of expectations regarding gender and emotional paths. On one hand, mostly recent literature positing that men's and women's emotions are not dissimilar would lead us to the expectation that there are no gender differences in the correlational structure of emotions. On the other hand, earlier studies, often based on the premise that women and men use disparate emotion management strategies (Hochschild 1989), occupy distinct emotional cultures (Cancian 1987; Hochschild 1979), and hold different sets of affective meanings (Lively and Heise 2004; Smith, Umino and Matsuno 1998) would lead us to expect that there are gender differences in the correlational structure of emotions that result in different shortest paths between emotions.

If such differences do exist, based on the above, one might expect emotional pathways to vary in terms of (1. length, (2. complexity, and (3. the transitional emotions used in the paths themselves.

Length: Women's shortest paths between negative and positive emotions are likely to be longer than men's shortest paths (e.g., their positive and negative emotions will remain further apart) (Cancian 1987; Hochschildl975; Lively and Heise 2004). In other words, women's more distant (e.g., positive and negative) emotions will remain more remote than men's, even taking into account the shortest paths between them. Additionally, the remoteness scores between similarly valenced emotions (that is, within negative emotions or within positive emotions) should also be greater for women and men.

Complexity: Women's shortest paths between positive and negative emotions are likely to require transitioning through more emotions than men's (Hochschild 1989). In other words, women may have to make more emotional transformations to achieve their shortest paths between distant emotions than their male counterparts.

Emotions: In terms of the emotional transitions themselves, women's shortest paths between distant emotions are likely to be marked by qualitatively different emotions than men's - specifically, women's shortest paths are more likely to entail emotions that are more positive and less powerful (e.g., "feminine emotions") than those used by men (Cancian 1987; Lively and Heise 2004; Heise 1979, 2007).6




Data and Methods

Data

The 1996 GSS (Davis and Smith 1996) employed a probability sample of 2,904 English-speaking adults residing in the United States. A random subset of 1,460 respondents was asked questions from the "emotions module" - 90 questions regarding emotion, including experiences in the past week with 19 different emotion states, details of anger episodes, and methods of emotion management. Respondents receiving the emotion module were given the following instruction for assessing recent emotional experiences. "Now I'm going to read a list of different feelings that people sometimes have. After each one, I would like you to tell me on how many days you have felt this way during the past 7 days." Although "restless" was included as one of the 19 emotion states in the GSS questionnaire, it is not included in these analyses, because it does not fit Ortony, Clore and Foss' (1987) definition of a pure emotional state.

Although the GSS (1996) emotions module remains the only national representative dataset containing information on a wide array of emotions, there are particular limitations to the data that must be addressed. One limitation is simply that there are only 18 emotions in these analyses and these eighteen fail to tap into any emotion that could be classified as unpleasant-dominant-quiescent (Morgan and Heise 1988; MacKinnon and Keating 1989), such as bitterness or disgust. In addition, the GSS (1996) data deal mainly with salient emotions -emotions that are memorable over a seven-day period and, thus, may under represent those less intense flashes of emotion that make up the tapestry of one's day to day emotional experiences. Finally, the data upon which these analyses are based are cross sectional and, thus, it is impossible to determine causality or even directionality (see Heise 1975). Therefore I am not proposing that emotions cause one another; rather, I am suggesting that one emotion can make possible the experience of some emotions and hinder others. I am also not proposing that these paths are more likely to lead to positive or to negative emotions, but, rather, that these paths exist between positive and negative emotions.

Methods

Because I am expanding Lively and Heise's earlier analyses of emotional segueing within the general population, I use the nine emotion factors that they derived jointly from a classification of emotions proposed by psychologists Ortony, Clore and Collins (1988) and insights from Affect Control Theory (Heise 1979; Smith-Lovin and Heise 1988). Ortony, Clore and Collins (1988) distinguish emotions that are reactions to events,



Emotional Segues * 919

agents, or objects, and propose that each kind of emotional reaction might be characterized by a number of different emotion tokens. For example, they propose that being pleased about a desirable event produces an affective condition of joy that might be recognized as feeling contented, happy, cheerful, delighted, ecstatic, etc. Further, the logic is that individuals experiencing, say, a general state of shame in the last week may have that affective state manifested in various specific emotions, so that they are more likely than others to report that they were embarrassed - or any of the other specific emotions that Ortony, Clore and Collins include under the affective condition of self-reproach.7 What distinguishes Affect Control Theory's perspective on emotion from

the Ortony-Clore-Collins classification is the delineation of emotion into the three fundamental dimensions of affective meaning: Evaluation, Potency and Activation. Affect Control Theory assumes that emotions, identities, attributes and settings that have similar EPA ratings are more similar to one another than they are to those that have dissimilar EPA profiles. By looking at the EPA ratings of each of the individual emotion states within each of the latent the factors and on the basis of their disparate activation values, Lively and Heise improved the overall fit of their confirmatory factor model by separating (over)joy from other emotions that they called tranquility and (out)rage from other emotions that they labeled anger Upon improving the fit of the measurement model to acceptable levels, they concluded that the Ortony, Clore and Collin's classification seemed to obscure differences in emotionality, by treating activation and intensity synonymously.8

Ihe Confirmatory Factor Model

In the structural equation analysis presented here, each affective condition is a latent variable, the specific emotions are indicators, and I empirically estimate the coefficients connecting latent variables and indicators. Given the emotion indicators that are available in GSS 1996, this analysis is limited to Ortony, Clore and Collins' (1988) event-based emotions (specifically the well-being emotions of joy and distress and the prospect-based emotions of hope and fear) and agent-based emotions (specifically the attribution emotions of pride and self-reproach and the compound emotion of anger). Table 1 provides additional details concerning these emotions in the Ortony, Clore and Collins classificatory scheme, plus the assignments of tokens from GSS 1996.9

Ortony, Clore and Collins (1988) did not mention the tokens of "calm" and "at ease" that were included in the GSS 1996 and that were identified as emotions by Ortony, Clore and Foss (1987). Though these two tokens are subjectively similar to "contented," they do not seem to fit in the category of joy (MacKinnon and Keating 1989; Morgan and Heise 1988).




a) n = 4 Consequently Lively and Heise (2004) 0 X established a supplementary category

O a) > -4 of tranquility to include them.

E 0_ a- ,> X o Results

E 0 -6 cn X r Table 2 shows the specifications and CD JK results of Lively and Heise's (2004)

, m Q) 0 " final measurement model, on which these analyses are based, for men and

women.10Forexample,calmwasusedas a U the scale-defining item for the tranquility

,,, x > latent variable by setting its factor coefficient to 1.0, and the data analysis estimated the factor coefficients for

X ; contented, at ease, and happy as 1.13, a CD : 1. 1 3 and .90, respectively. Latent factors

were allowed to co-vary freely. Error (10 - O _ : . terms for the individual indicators were

.oOU assumed to be uncorrelated. Results Q CD .- V for male respondents appear in Model

; g 1, whereas the results for females are

(U .> C ) ,= Q found in Model 2 (all coefficients are Da) significant at the .00 level). 7 $ Overall the model fits both the male

a $ >, and female data reasonably well, as

- Ca) -O = U s = shown by most of the goodness-of-fit

o~ ~ c o indicators at the bottom of the table.11 0~

a) u 0 E a-, The ratio of chi-square to degrees of C E a X C cu ^cE freedom, which is often used in place

C? En a) ? a)s -0 = of the chi-square value as a measure of - C a_ ? 5 fit when dealing with large samples, is

C E C s ?E 2.13 for the male data and 2.38 for the o ? X -) 0 o ? female data, both well within the value

a) co X D 3 O C ? = t of 3.00, which is frequently accepted _j > a)nx Dz =) cu cm > as the maximum value indicating

= QO O @ @ O : w ^ 0an acceptable fit (Kline 1998:128).

._ C] CD Q) W o 4

* Additionally, the incremental and the . U < comparative fit indices reach .90 for

0o . the male data, the standard value for ; o < < | acceptance, although both of these

~ _ ,eindices fall slightly short of .90 for the

c C 0 oaa U.m-,0 female data (both at .88). The Root




Table 2: Factor Coefficients of Emotion Items in Measurement Model, by Men and Women

Factor Coefficients Mean EPA Profiles Emotion Factor Male Female Male Female

Calm Tranquility 1.00 1.00 At ease Tranquility 1.13 1.17 Contented Tranquility 1.13 1.16 2.10,1.47,.13 2.57,1.65,.12 Happy Tranquility .90 1.03 (1.75,1.63,1.64) (1.51,1.71,1.66)

1.83, 1.54,1.27 2.74, 1.74, 1.98 Overjoyed Joy 1.00 1.00 (1.91,1.96,1.87) (1.37,1.83,1.92)

2.23,1.98, 2.19 2.89, 2.54, 2.89 Excited Hope 1.00 1.00 (1.50,1.36,1.33) (1.35,1.47,1.51)

2.15, 2.10, 1.53 2.38, 2.34, 1.86 Proud Pride 1.00 1.00 (1.18,1.54,1.09) (1.30,1.52,1.58) Embarrassed Self-reproach 1.00 1.00 -1.45,-1.27,-1.06 -2.01, -1.41, -1.47 Ashamed Self-reproach .58 1.22 (1.91, 1.96,1.87) (1.60, 2.18, 2.09) Fearful Fear 1.00 1.00 Worried Fear 1.78 1.65 -1.31, -.79,-.17 -1.32, -.88,-.10 Anxious-tense Fear 1.54 1.40 (1.70, 1.90, 2.03) (1.85, 2.10, 1.95) Sad Distress 1.00 1.00 Blues Distress 1.09 1.05 -1.95, -1.66, -2.01 -2.23,-1.67,-2.21 Lonely Distress .80 1.00 (1.64,1.97,1.70) (1.49,1.96,1.48) Angry Anger 1.00 1.00 -1.15, -.21, .90 -1.86, -.30, 1.07 Mad Anger 1.07 1.03 (1.64,1.97,1.70) (1.36,1.59,1.49)

-1.34,0.27, 1.56 -1.95,.11,.80 Outraged Rage 1.00 1.00 (1.93, 2.20,1.75) (1.41,1.87,1.52) Goodness of Fit Measures Chi-Square/df 2.13 2.38 Incremental fit index .90 .88 Comparative fit index .89 .88 RMSEA .03 .03

Note: EPA profiles were obtained from the Interact Dictionary (www.indiana. edu/-socpsy/ACT/interact.htm); Ns range from 27 to 39 per EPA Profile.

Mean Square Error of Approximation is .03 for both males and females suggesting that the model's ability to reproduce indicator covariances for both sexes is acceptable.

Also in Table 2 are the EPA profiles (along with their standard deviations) for each of the latent factors in the model, for women and men. These profiles were derived by taking the mean of the EPA profiles and standard deviations for each of the emotion indicators in the model - for example, I averaged the EPA profiles and the standard deviations for shame and embarrassment to create the mean EPA and mean standard deviation for the latent factor self-reproach.12




Table 3: Relations among Emotion Factors for Men and Women 1 2 3 4 5 6 7 8 9

1. Tranquility - .41* .23* .23* -.19* -.35* -.33* -.63* -.72 *A 2. Hope .37* - .43* .35*A .03 -.04 -.06 -.10* -.10* 3. Joy .25* .48* .38* .11*A .05 .06 .08* .00 4. Pride .14* 46*A 41 * - 4A .12* .02 A 09* A ooA 5. Self-reproach -.29* .13* .24*A .19*A .19*A .08*A 43*A 30*A 6. Anger -.35* .04 .04 .1 5* 53* A .61 *A .59* .48* 7. Rage -.28* .08* .11* .17*A .38*A .77*A .46* .48* 8. Fear -.62* .02 .11* .23*A .60*A .63* .54* - .83* 9. Distress -.64*A _.09* .07 .18*A .58*A .48* .44* .80*

Note: For Men (Lower Triangle; N = 597) and Women (Upper Triangle; N = 764) *Correlations are significantly different from zero at the .05 level. ARelationships differ significantly by sex at the .05 level in a two-tailed test based on Student's t after Fisher's r to z transformation (Winkler and Hays 1975:653).

Table 3 shows the correlation matrix for the nine latent emotions: tranquility, hope, joy, pride, self-reproach, anger, rage, fear and distress, with women represented in the upper triangle and men in the lower.13 Again, emotions that are correlated positively are expected to be more readily accessible to one another than emotions that are negatively correlated. As might be expected, given their greater similarity, correlations within unpleasant emotions and correlations within pleasant emotions generally are higher than the correlations between pleasant and unpleasant emotions for both groups. However, correlations between pleasant and unpleasant emotions are not simply negative for either group. Women have four pairs of positive-negative emotion correlates that are positively related with correlations significantly different from zero at the .05 level,

whereas men have more than twice that number. These correlations are presented visually in Figure 2.14

In the female sample, pride correlates positively with anger and fear, while joy correlates positively with fear and self-reproach. In the male sample, however, pride correlates positively with self-reproach, rage, distress, fear and anger; joy is correlated positively with self-reproach, rage and fear; and hope with self-reproach and rage. Moreover, nine of the ten positive correlations between positive and negative emotions in the male sample are twice, and in some cases thrice, the magnitudes of those found in the female data and are statistically different at the .05 level. Additionally, men's experiences of pride and hope are correlated more positively than women's, while women's experiences of tranquility and distress are correlated more negatively than men's (all are significant at the .05 level).

Based on the assumption that emotions correlating positively during a weeklong period may be relatively accessible from each other and




Figure 2. Positive Correlations between Positive and Negative Emotions

Female Data (N = 764)

Pride Joy

Anger Fear Self-reproach

Male Data (N = 597)

| Pride || Joy || Hope |

Distress Anger Fear Rage Self-reproach

Note: (p < .05), by Women and Men

emotions correlating negatively may be relatively inaccessible and that these correlations have implications for emotion management (Lively an Heise 2004), 1 offer an index of remoteness based on correlation coefficients to quantify this notion more exactly (see Table 4 for the formula). If two emotions correlate 1.0 then they have a remoteness of 10; and if they correlate -1.0 then they have a remoteness of 20. In-between correlations are curvilinearly related to remoteness; for example, a correlation of .5 gives a remoteness of 3.15

Table 4 shows the results of shortest-path analyses of the correlations presented in Table 3 (with female data, again, represented in the upper triangle and male data in the lower). In graph theory, the simple source shortest-path problem is that of finding a path between two vertices such that the sum of the weights of its constituent edges is minimized. The shortest paths presented here were generated by Dijkstra's algorithm - a model that solves single source problems if all edge weights are greater than or equal to zero (Corman, Lesierson, Rivest and Stearn 2001). As noted previously, the remoteness scores signify the relative distance between two emotions and may serve as a marker of the emotion management effort required to move from one emotion to another. Based on the notion that small shifts in similar emotions are more manageable




than large leaps between dissimilar ones the shortest paths (reported in parentheses) use shortcuts via intervening emotions that reduce the remoteness between less accessible emotions.

Consistent with first hypothesis (Length), it appears that the shortest paths between positive and negative emotions may be longer for women than for men, even when segueing via similar emotions. Specifically, men's shortest path between fear and hope (via self-reproach) yields a remoteness of 8, whereas women's (via joy) yields a remoteness of 10. Similarly, the shortest path for men between self-reproach and tranquility (via joy)

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yields a remoteness of 10, while the shortest path between self-reproach and tranquility (also via joy) yields a remoteness of 12. To the degree that remoteness scores signal the amount of work or effort that it takes to move from one emotional state to another, these findings suggest that women's transitions from negative to positive emotions (as well as vice versa) may be more difficult (or require more cognitive or behavioral effort) than those same transitions for men.

Additionally, there is considerable variation in the remoteness scores between positive and negative emotions that do not require additional transitions. For example, men's shortest paths between pride and all negative emotions - that is, self-reproach, anger, rage, fear and distress are all significantly shorter than women's same paths. Men's shortest paths between self-reproach and hope, joy and pride are also significantly shorter than women's shortest paths between the same emotions.

A similar pattern emerged when examining the remoteness scores between negative emotions, though the scores that occur between positive emotions are less consistent. Among negative emotions, men's shortest paths between self-reproach and anger, rage, fear, and distress are all significantly shorter than women's. Similarly, the remoteness score for men's transition between anger and rage is half that of women's. Although the overall pattern holds when examining the differences in shortest paths between hope and pride (men have a remoteness score of 3, compared to women's score of 4), men's shortest path between pride and tranquility yields a remoteness score of 6, whereas women's yields a score of 5 (p < .05). Notably, pride and tranquility is the only set of emotions that yields a shorter shortest path for women, compared to men.

In addition to generally being longer, women's shortest paths - at least those that occur between the more distant positive and negative emotions - also appear to be more complicated than those for men, a finding that is consistent with the second hypothesis (Complexity). The shortest path between tranquility to distress (or vice versa) for males can be accomplished by invoking a single intervening emotion: pride, whereas the same shortest path for women entails segueing between two emotion states: fear and joy. Men's shortest path between distress and hope can also be accomplished with the invocation of a single emotion state: self-reproach, whereas it takes two intervening states (again, fear and joy) for women to achieve the same goal. Finally women's shortest path from distress to joy is achieved via fear (reducing the remoteness from 11 to 8), while the shortest path for men requires no intervening emotion (remoteness of 7); a similar pattern is found when examining the shortest paths between rage and hope.

It is worth noting that the majority of pathways marked by intervening variables are also qualitatively different. Consistent with the third hypotheses




(Emotion), the structure of men's and women's emotional experience is sufficiently distinct that their shortest paths are marked by different emotions most of the time. Generally speaking, the shortest paths between men's negative and positive emotions typically involve the emotions pride or self-reproach, whereas the shortest paths between women's disparate emotional states typically involve feelings of joy, fear or some combination of the two. In particular, three of men's shortest paths are marked by pride, two by self-reproach and only one each by hope and joy. Although joy plays only a minor role in men's shortest paths, it marks seven of women's paths, though two of these paths feature joy accompanied by fear. And unlike men, whose paths are marked most commonly by pride, women only have one shortest path that uses pride, (i.e., the path between anger and tranquility). The EPA values of pride (men's most common segueing emotion) and joy (women's most common segueing emotion) are 2.15, 2.10, 1.53 and 2.74, 1.74, 1.98, respectively.16

The EPA profiles and standard deviations presented in Table 2 provide some support for the expectation that women may be more likely to use more positive and less powerful emotions: women's affective understanding of the relative goodness of joy (2.74) is significantly more positive than men's affective conception of the relative goodness of hope (2.23; p < .05) - the two emotions that represent, respectively, women's and men's shortest paths between tranquility and rage. A similar pattern occurs when examining women's affective understanding of the relative goodness of joy vs. men's affective understanding of the relative goodness of pride (2.15; p < .05) - the two emotions that comprise women's and men's shortest paths between fear and tranquility. Finally, women's shortest path between hope and fear uses joy, an emotion that women view as significantly more positive (2.74) and powerful (1.74) than men view their transitioning emotion of self-reproach (-1.45, -1.27; p < .05) between the same two states. Notably, women also view joy as significantly more active (1.98) than men view self-reproach (-1.06; p < .05); this shortest path, however, is the only one that differs significantly in terms of potency and activation.

Discussion

The relationship between gender and emotion has long fascinated social scientists. Although early studies pointed to gender as an influencing factor in the experience of emotion, more recent studies of emotional outcomes have challenged the central role of gender in understanding the distribution of emotional experience and expression. But non findings regarding the effects of gender on single indicators of emotional experience do not mean, definitively, that there are no gender differences




in the experience of emotion. Indeed, a look at the correlational structure of emotional experience suggests something else entirely.

Consistent with the idea that women and men occupy different emotional spheres (Cancian 1987) and the observation that women's affective meanings are more disperse than men's (Lively and Heise 2004), women's shortest paths between positive and negative emotions appear to be longer then men's, even after segueing through intervening emotions (Length). This general pattern holds even for movement between similarly valenced emotions. Moreover, consistent with observations of men's and women's disparate coping strategies (Hochschild 1989), men's distant emotions appear to be more easily accessible to one another than are women's (Complexity). That is, it appears that women move through more intervening emotions than men to make the same emotional transitions (e.g., from distress to tranquility). Finally, the expectation that women's and men's shortest paths may be marked by different emotions is also supported. In particular, women tend to use more positive and, and on some occasions, less potent and less active emotions to make emotional transitions (Emotions); specifically, their pathways tend to be more frequently marked by joy and fear as opposed to pride and self-reproach.

These findings suggest that women, in the course of a seven-day period, may be more likely to find themselves either mired down in negative emotions or, conversely, mercifully content in positive ones, whereas men may be more likely to move between positive and negative states. Even women's transitions through similarly valenced emotions seem to require more effort than men's transitions through the same feelings. Furthermore, women's shortest paths for emotion management may be more difficult to accomplish than men's and, as a result, less likely to succeed. They also require the elicitation of qualitatively different emotions.

Despite recent claims that gender is not a significant predictor of emotional experience, at least as it relates to the likelihood of experiencing or expressing particular emotions, gender nonetheless has real implications for more subtle aspects of emotion - e.g., how emotions co-occur - and, potentially, pathways of emotion management. These findings may provide us with insight into how the process of emotion management operates and offer clues into why women are consistently found to have higher rates of depression than men in a seven-day period (i.e., women's shortest paths from distress to positive emotions involve additional intervening emotion states that still yield higher degrees or remoteness).1' They may also illuminate Simon and Nath's (2004) recent findings that women's self-reported anger is of longer duration than men's (i.e., all of women's shortest paths leading into or out of anger are equal to, if not longer than [four out of eight], those of their male counterparts).




Recent studies suggest that the influence of gender and emotion may have waned over the years, particularly following WWII and the women's movement (Heise 2007). However, much of the recent research has been limited to the investigation to absolute outcomes. This investigation hopes to re-orient scholarly work on gender and emotion, and on emotion more generally, to the importance of understanding how emotions co-occur. This idea is not new, but, in fact, is consistent with current lines of research in such fields as mental and physical health and juvenile delinquency, which focus less on individual behaviors or conditions, and more on co-morbidity (Rosenfield, Phillips and White 2006).

Having said this, two caveats should be addressed. As mentioned before, self-report data may be tapping into individuals' most salient or most memorable emotional experiences, as opposed to the entirety of their experiences. This suggests that the pathways reported here may be memory structures rather than emotional structures; indeed, affect control theory (Heise 1979) builds in memory through its reliance on fundamental and transient sentiments. Even if these findings reflect memory rather than emotional transitions, the pathways nonetheless suggest that emotion memories are stored in ways that are consistent with cultural differences in women's and men's sentiments, coping strategies, etc. Although it is beyond the scope of this particular study to determine whether the items are tapping into real emotion or emotional memory, the concern raises the need to collect data (1. over a shorter period of time or (2. in real time. Such an undertaking could use diary methodology, where subjects are routinely asked to write down emotional experiences or reactions randomly throughout the day. Another strategy would entail creating multiple emotional experiences in experimental settings that could be measured in real time (Robinson, Rogalin and Smith-Lovin 2004).

A second caveat to this work is the fact that it only relates to gender differences broadly defined, without taking into account variation within each group. To the degree to which gender is an institutionalized arrangement based in large part on power and status, the effects of gender, considered alone, may be overstated (Ridgeway and Smith-Lovin 1999). However, even recent studies of gender and emotional outcomes found fewer main effects of gender than might have been expected given scholars' earlier focus on gender (Simon and Nath 2004). Future work in this area would need to determine whether the emotional paths of women remain different than those of men once other social characteristics and structural considerations have been taken into consideration. For example, do the emotional pathways differ for male and female executives? To what degree, if any, do emotional pathways differ for mothers and fathers? Do they for women and men of different racial and ethnic backgrounds?




In addition to examining gender in tandem with other social characteristics or other social statuses, this method of analysis should also be applied to better understanding how emotional pathways may vary along other important social characteristics the most obvious, at least pertaining to emotion, being race (Mabry and Kiecolt 2005; Harlow 2003), age (Schieman 1999) and education (Schieman 2000). Less obviously, further studies of this genre should also address how emotion pathways are affected by holding particular social roles (Evenson and Simon 2005), ideologies (Kroska 2002) and even occupations (Hochschild 1983).

Given the important role that affective meaning seems to play in emotional segueing, another area ripe for this type of analyses would be the examination of cross-cultural or sub-cultural variations in emotion management. Building on the work of Heise and Morgan (1988) and MacKinnon and Keating (1989), Smith and colleagues have headed an ambitious project that has documented numerous subtle variations between the affective sentiments of Americans and Japanese (Smith and Francis 2005; Smith, Matsuno and Ike 2001; Smith, Matsuno and Umino 1994), between Americans and Chinese (Smith 2002), and between Japanese women and men (Smith, Umino, and Matsuno 1998). Smith-Lovin and Douglass (1992) have also reported notable sub-cultural differences in affective meaning when examining sentiments among members of two distinctive identity groups. Given the degree to which sentiment structures are culturally influenced - as well as their apparent roles in emotional segueing - it is likely that the shortest paths between emotions may also be culturally specific.

Although limited to main effects of gender only, this study reorients us to the importance of gender by revealing that women's and men's emotional experiences correlate in different ways. And, although relatively subtle, these differences seem to have real implications for the duration of emotional experiences, as well as the nature and effectiveness of emotion management strategies. Sociologists, to date, have paid little attention to how the structure of emotional experience may vary as a result of group membership or how these differences may impact one's emotional well being. The variations between men and women reported here are, in part, consistent with patterns of difference documented in brain research which show that a more dispersed area of the brain is activated among women than men when emotional stimuli is introduced (Baving et al. 2003; Hofer et al. 2006). Correlational differences in men's and women's emotions may, however, also be attributable to larger social arrangements, subcultural variation in affective sentiments or even preferred methods of emotion management. As sociologists continue to cultivate an understating of how social characteristics affect individuals' emotional lives, future research may need to consider the ways in which the structure of emotions vary as




well as to formulate more systematic understandings of why and to what ends such differences may or may not occur.

And finally, to the degree that correlations seem to coincide with efficacious means of coping or emotion management, further analyses of them and their corresponding shortest-paths may allow us to uncover systematic differences in emotion management styles, both personally and interpersonally. From a practical standpoint, such an occurrence might allow us to determine which styles are more efficient and effective. Moreover, from an equity standpoint, does women's utilization of emotion management pathways marked by weaker emotions lower their status, particularly in interactions in the work place, where laboratory and ethnographic studies alike reveal that individuals who exhibit powerful emotions are more likely to be attributed more status or judged as being of higher status (Tiedens 2000)?

These observations lend themselves to further empirical questions, such as whether women would benefit from using male paths, even though it might mean claiming (and thus transitioning through) stereotypically

male emotions? If these pathways are social (and therefore learned) can individuals be re-socialized to use more effective emotion management strategies - strategies that might, in turn, reduce frequent experiences of distress and to make more frequent feelings of well-being (marking the poles of emotional experience) even if it means claiming emotions that are typically - or culturally and, perhaps, structurally - off limits? To what degree may some groups be disadvantaged in the sense that they are normatively prohibited from using shorter pathways (e.g. pride and self reproach)? These questions are beyond the scope of the data presented here. They may, however, have the potential to set an agenda that allows researchers to bridge the disparities within research on gender differences in emotion. They may also push our understanding of yet another way one's social location influences one of the most intimate and seemingly individual aspects of one's life.

Notes

1. See MacKinnon and Keating (1989), Morgan and Heise (1988) and Osgood, May and Miron (1975) for a more detailed discussion of the three underlying dimensions of affective meaning, which are typically labeled Evalation, Potency and Activation.

2. Although the political examples cited here suggest that emotional segueing can occur over a short period of time (e.g., within the space of an hour), the

therapeutic examples reveal that emotional segueing can also occur over a

longer period (e.g., over a period of weeks).




3. Simon and Nath (2004) also examined the 19 emotion items in the GSS using factor analyses; however, they stopped short of examining how these factors correlated with one another.

4. See Lively and Heise (2004) for details regarding the actual measurement model, which was derived from insights taken from Ortony, Clore and Collins'

(1988) emotional classification, Affect Control Theory (Heise 1979; Smith Lovin and Heise 1988).

5. EPA profiles for the single indicators found in the GSS were taken from the

computer program Interact and then averaged, using both male and female data. Interact can be found at http://www.indiana.edu/~socpsy/ACT/interact/ Javalnteract.html. Ancillary analyses, not shown here, reveal that women's affective meaning is notably more dispersed then men (also see Lively and Heise 2004). For instance, the EPA profiles for happy and blue for men are 2.92, 2.43, 1.96 and -1.88, 1.66, -2.06, respectively. The same values for women are 3.58, 2.80, 2.50 and -2.05, 1.82, -2.27.

6. According to Affect Control Theory, women view the social identity of female as significantly more positive (in terms of Evaluation) and significantly less

powerful (in terms of Potency) than men view the social identity of "male." There is no significant difference, however, between men's affective sentiments regarding "male" and women's of "female" in terms of Activation

(http://www.indiana.edu/~socpsy/ACT/interact.htm), which implies that women are no more likely than men to experience active emotions and vice versa (Lively and Heise 2004).

7. Although Lively and Heise (2004) used the Ortony-Clore-Collins classification because it is especially systematic and inclusive, they did so with one essential caveat: the Ortony-Clore-Collins definition of distress focuses only on

depression as reflected in the Center for Epidemiological Studies Depression Scale (Mirowsky and Ross 1995), without incorporating feelings associated with

anxiety. In order to be consistent, I also use the term distress in my analyses.

8. See Lively and Heise (2004) for more details regarding the steps they took in

creating the final measurement model, which was derived from insights taken from Ortony, Clore and Collins' (1988) emotional classification and affect control theory (Heise 1979; Smith-Lovin and Heise 1988).

9. Following Lively and Heise's (2004) original model, I do not claim to match the Ortony, Collins and Collins (1988) scheme, but merely to use it as a

theoretically principled starting point. So, although the "hope" indicator in the

Ortony-Clore-Collins classification refers to "being happy about an event" and the GSS questions asks more generally if one is excited "about something," they are interpreted as being sufficiently close.

10. Given that all of the emotion items were highly skewed (Lively and Heise 2004), I estimated the model using asymptotically distribution free estimation in AMOS 4.0. Unlike maximum-likelihood estimation, which assumes a normal distribution, ADF does not impose an assumption of normality and typically generates reliable estimates in large samples




(Browne and Cudeck 1992). The estimates using ADF estimation and ML estimation were largely similar.

11. The Incremental Fit Index estimates how well the model fits in comparison with a baseline model of independence (Bollen 1989); the IFI statistic is

preferable to other similar measures when using estimators that do not assume normality in the data (Hoyle and Panter, 1995). The Comparative Fit Index also assesses the reduction in the amount of misfit of the target model relative to the baseline model (Hu and Bentler 1995). The Root Mean Square Error of Approximation was developed by Steiger and Lind ( 1980) as a means for compensating for the effect of model complexity. According to Browne and Cudeck (1992) a value of the RMSEA of about .05 or less would indicate a close fit of the model in relation to the degrees of freedom. Although this

figure is based on subjective judgment, they argue that it is more reasonable than the requirement of exact fit with the RMSEA = .0.

12. The EPA profiles, standard deviations, and Ns for each of the individual emotion items are available from the author.

13. AMOS yields correlations that are sometimes higher than zero-order correlations among indices, a standard result when creating latent trait models. In keeping with Lively and Heise's (2004) original analyses, I used AMOS estimates for the correlations rather then computing actual scores and

correlating them.

14. Given the significant differences in correlations between women and men, as

expected, auxiliary models that do not differentiate between the two groups have a somewhat reduced fit.

15. The remoteness scale creates arbitrary values. I used Lively and Heise's (2004) formula for the ease of comparability.

16. The EPA value for pride was taken from the male dictionary and the value for

joy from the female dictionary.

17. See Mirowsky and Ross (1995, 2003) and Simon (2007) for more detailed discussions of the relationship between gender and depression.

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