Predicting the Strategic Identity Management of Gender and Race

Abstract

Two questionnaire studies examined when people strategically claim (i.e., use positive distinctiveness) or downplay (i.e., use social recategorization) socially devalued identities (gender for women in science in Study 1; race for Black medical students in Study 2). The results of both studies indicated that perceiving one's group to be devalued was related to reported use of both strategies, and identification with the devalued group was related to less social recategorization use and greater positive distinctiveness use. Only the Study 2 results demonstrated that identification with an alternate, socially valued identity (i.e., medical professional) was positively related to social recategorization use. Additional measures included in Study 2 indicated that general impression management concerns were related to the use of both strategies, and that positive distinctiveness use was related to less depression and more positive medical career attitudes. These findings contribute to understanding how different people attempt to manage others' perceptions of their socially devalued group.

Notes

¹Analyses were conducted to assess whether women who chose to participate in Wave 2 significantly differed on the key variables from women who chose not to participate. Although the women who chose to participate in Wave 2 (mean age = 21.75, SD = 2.87) were marginally younger than those who chose not to participate (mean age = 22.49, SD = 4.03), t(333) = 1.90, p = .06; and Wave 2 tended to have a smaller percentage of people of color (36% vs. 45%), χ²(1) = 3.14, p = .08; the two groups of women did not significantly differ on science centrality at Time 1, t(334) = −0.59, p = .56; gender centrality at Time 1, t(335) = −0.91, p = .36); discrimination due to being a scientist at Time 1, t(333) = −0.24, p = .81; or gender discrimination at Time 1, t(335) = 0.77, p = .44).

²In order to examine whether interaction effects might be present, we tested two additional multiple regression models for each dependent variable. The interaction between gender centrality and science centrality, or the interaction between gender centrality and gender discrimination, was added on the third step of the analysis as a predictor of social recategorization and positive distinctiveness. Neither the interaction between gender centrality and science centrality (for social recategorization, B = .00, β = .00, SE = .04, p = 1.00; for positive distinctiveness, B = .00, β = .01, SE = .04, p = .92) nor the interaction between gender centrality and gender discrimination (for social recategorization, B = .02, β = .10, SE = .02, p = .25; for positive distinctiveness, B = −.00, β = −.02, SE = .02, p = .85) were significant.

*p < .05.

**p <.01.

†p < .10.

*p < .05.

**p < .01.

†p < .10.

³In order to test for interaction effects in this sample, we again tested two additional multiple regression models for each dependent variable. The interaction between racial centrality and professional centrality, or the interaction between racial centrality and perceived stereotyping, was added on the fourth step of the analysis as a predictor of social recategorization and positive distinctiveness. Neither the interaction between racial centrality and professional centrality (for social recategorization, B = .02, β = .04, SE = .03, p = .60; for positive distinctiveness, B = .04, β = .07, SE = .04, p = .29) nor the interaction between racial centrality and perceived stereotyping (for social recategorization, B = .01, β = .01, SE = .03, p = .82; for positive distinctiveness, B = .00, β =.03, SE = .03, p = .99) were significant.

*p < .05.

**p<.01.

†p < .10.

*p < .05.

**p < .01.

†p < .10.

**p < .01.

†p < .10.

*p < .05.

**p < .01.

*Items in parentheses are from the Gender-Based Impression Management Scale.