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Record W4323928780 · doi:10.1002/job.2702

Can a familiar gender stereotype create a not‐so‐familiar benefit for women? Evidence of gendered differences in ascribed stereotypes and effects of team member adaptivity on performance evaluations

2023· article· en· W4323928780 on OpenAlexfundno aff
Joseph A. Carpini, Aleksandra Luksyte, Sharon K. Parker, Catherine Collins

Bibliographic record

VenueJournal of Organizational Behavior · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSituational ethicsInterdependencePsychologySocial psychologyStereotype (UML)ScholarshipWork (physics)Political science

Abstract

fetched live from OpenAlex

Summary Our research examines the differential effects of stereotypically feminine work behavior—team member adaptivity—on performance evaluations. Team member adaptivity requires being accommodating to changing relational and situational demands to achieve interdependent work goals. As such, women who engage in team member adaptivity will be recognized and rewarded more in their performance evaluations compared to men. We tested our model across three studies. As hypothesized, the results of Experimental Study 1 ( N = 600) demonstrated team member adaptivity is subject to a gendered stereotype and ascribed to women more so than to men. Building on this finding, Field Study 2 ( N = 96) demonstrated that team member adaptivity was positively related to performance evaluations for women but not for men. Study 3 used multi‐source dyadic data obtained from managers and their supervisors ( N = 141) and demonstrated that women who engage in team member adaptivity receive more favorable performance evaluations than their male counterparts. Together, these studies demonstrated the benefits of team member adaptivity for women more so than for men. This research extends our understanding of social role theory as well as the outcomes of adaptive performance while also offering several avenues for future scholarship with the potential to address ongoing gender inequities in the workplace.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.342
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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