Perceptions of and by Women in a Military Setting: The One-with-Many Design Deborah A. Kashy Michigan State University

The One-with-Many Design A person is in multiple dyads, but each partner is in a dyad only with that person The One is the focal person The Many are the partners Blend of the standard dyadic design and a Social Relations Model design In the intergroup context, the focal person may be a member of one group (e.g., a woman), and the partners may be members of another group (e.g., men)

Distinguishable case: Partners can be distinguished by roles e.g., family members (Mother, Father, Sibling) Typically assume equal # of partners per focal person

Indistinguishable case: All partners have the same role with the focal person e.g., students with teachers or manager with workers No need to assume equal N

Who provides the data? 1PMT = 1 perceiver, many targets Focal person provides data for each partner E.g., teacher rates each child on agreeableness

1PMT: Focal person provides data with respect to the partners Source of nonindependence: Actor effect: tendency to see all partners in the same way

Who provides the data? MP1T = Many perceivers, one target Each partner provides data for the focal person E.g., each student in a class rates the teacher

MP1T: Partners provide data Source of nonindependence: Partner effect - tendency of all partners to see the focal person in the same way

Who provides the data? Reciprocal or 1PMT-MP1T Data are collected from both the focal person and the partners E.g., Teacher rates the students AND students rate the teacher

Indistinguishable case: All partners have the same role with the focal person Sources of nonindependence More complex…

Sources of nonindependence in the reciprocal design Individual-level effects for the focal person: Actor & Partner variance Actor-Partner covariance Dyadic effects Relationship (plus error) variance Dyadic reciprocity covariance

Data Analytic Approach for estimating variances: 1PMT FocalIDPartIDDV Estimate a basic multilevel model in which There are no fixed effects with a random intercept. Y ij = b 0j + e ij b 0j = a 0 + d j The variance of the random intercept estimates actor variance MIXED dv /FIXED = | SSTYPE(3) /PRINT = SOLUTION TESTCOV /RANDOM INTERCEPT | SUBJECT(focalid) COVTYPE(VC).

SPSS output for 1PMT Covariance Parameters Fixed Effects So the absolute actor variance is.791, and % is.791/( ) = 39.5%

Data Analytic Approach for estimating variances & covariances: The Reciprocal Design A fairly complex multilevel model… MIXED motivated BY role WITH focalcode partcode /FIXED = focalcode partcode | NOINT SSTYPE(3) /PRINT = SOLUTION TESTCOV /RANDOM focalcode partcode | SUBJECT(focalid) covtype(un) /REPEATED = role | SUBJECT(focalid*dyadid) COVTYPE(UN). (Please see handout)

Example: Perceptions of and by Women in the Texas A&M Corps of Cadets University/ROTC organization similar in structure to VMI or the Citadel Established in 1876 Today Includes about 2000 students (about 5% of Texas A&M student body) Approximately 94% male at time of data collection ( )

History of Women in the Corps Participation in the Corps of Cadets opened to women. 50 women join, organized into an all female unit. The members referred to derisively as "Waggies Female cadets are allowed to participate in the Bonfire cut. not allowed to cut any tree bigger than 12 inches in diameter, worked in a separate area from the men. In past, women were only allowed to work as members of the "Cookie Crew" or as "Water Wenches." Women integrated into all Corps organizations

The One-with-Many Corps data

Method Participants Full Study: N = 380 (353 Men & 27 Women) Todays data: 21 women with 101 partners Number partners per woman varies from 3 to 19 Procedure Met with Corps leaders Individual lunches with First Sergeant of each outfit Data collection at weekly outfit meetings

Measures Ps rated each member of their class and outfit, including themselves, on 14 dimensions relevant to success in the Corps (9-point scale) Motivation dedicated, physically fit, diligent, motivated Leadership good leader, self-confident Character integrity, selfishness(R), tactful, respects authority, arrogant(R) Masculine Masculine, Feminine (R)

Variance partitioning results VariableWoman as Actor Variance % Woman as Partner Variance % Motivated.98* *32.3 Character1.14* *31.7 Leadership.70* Masculine.20* The woman-as-actor variances indicate significant assimilation in perceptions of their male partners. The woman-as-partner variances indicate that there was significant consensus on the womans attributes.

Reciprocity Correlations Generalized Women who generally saw men as more motivated (& higher character) were seen by men as more motivated (& higher character). For leadership, women who saw men as higher in leadership were perceived to be lower in leadership Dyadic If the woman saw the man as uniquely high in character, he tended to reciprocate. If the woman saw the man as uniquely high in masculinity, he tended to see her as uniquely low in masculinity (i.e., more feminine). VariableGeneralizedDyadic Motivated Character Leadership Masculine.na-.175 Note that none of these correlations are statistically significant

Differences in Mean ratings of outgroup perceptions Women saw the men in their outfits in a more positive manner than the men saw the women. Variable Womans rating of male partners Mens rating of female focal persont Motivated ** Character Leadership ** Masculine **

Differences in Womens self-ratings and the average of the mens perceptions of those women Men, on average, rated women significantly lower in motivation and leadership than women rated themselves. The difference for character was marginally significant. VariableMens rating of female focal person Womans self ratingst(20) Motivated ** Character Leadership ** Masculine

Differences in mens mean self-ratings and the average of the womens perceptions of those men Women, on average, rated men significantly lower in character and leadership than men rated themselves. BUT the differences are smaller than for women VariableWomans rating of male partners Mens self ratings t Motivated Character * Leadership ** Masculine

Self-other slopes: Do men see women as they see themselves (& vice versa)? VariableWomens Self predicting mens ratings of women Slope Mens Self- ratings predicting womens ratings of men slope Motivated.352*.307** Character ** Leadership.392*.394*** Masculine * Both men and women show some self-other agreement.

Discussion The Corps results indicate that Women are not perceived to be as successful as men in the corps. Variance partitioning suggests that there is consensus among the men concerning which women are more successful and which are less successful The correspondence between the womens self- perceptions and how they are seen by men suggests that women agree with men about their level of success.

What makes the one-with- many design unique Ability to estimate focal persons behavioral and perceptual consistency across partners. Ability to estimate Consensus when partners provide data concerning focal person Ability to estimate both Generalized and Dyadic reciprocity when both focal person and partners provide data

Thanks! Thanks also to Jennifer Boldry Wendy Wood The Texas A&M Corps of Cadets