MétaCan
Menu
Back to cohort
Record W3023643759 · doi:10.1080/13678868.2020.1749493

A meta-analytic review of gender composition influencing employees’ work outcomes: implications for human resource development

2020· review· en· W3023643759 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Resource Development International · 2020
Typereview
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsWestern University
Fundersnot available
KeywordsHuman resourcesHuman resource managementMeta-analysisWork (physics)PsychologyComposition (language)Career developmentBusinessKnowledge managementManagementSocial psychologyComputer scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

Drawing from Kanter’s tokenism theory, the current meta-analysis provides a statistical synthesis of the research linking gender composition of the workplace to men and women’s evaluative (leadership, rewards, and performance) and affective (interpersonal relationships, stress, and attitudes towards women) outcomes. In addition, we examine the moderating effect of task gender-type on these relationships. Evidence for simple gender composition effects was weak, with only men’s interpersonal outcomes being associated with gender composition. In contrast, we found strong evidence supporting the moderating effect of task gender-type on these relationships for both sexes, across several of the outcomes. Notably, the strongest moderator effect was shown for men’s leadership, with a clear pattern demonstrating that gender composition has a stronger positive effect on this outcome for men performing gender-neutral tasks, compared to men performing masculine tasks. This underscores the importance of task gender-type as a more powerful indicator of workplace gender norms than a numerical representation of men and women. Despite progress towards gender parity in the workplace, gender hegemony remains strong in male-typed tasks as they stand impervious to the effects of gender composition. Results are discussed in light of tokenism theory and its implications on designs of HRD interventions.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.516
GPT teacher head0.443
Teacher spread0.074 · 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