Interventions on gender equity in the workplace: a scoping review
Bibliographic record
Abstract
BACKGROUND: Various studies have demonstrated gender disparities in workplace settings and the need for further intervention. This study identifies and examines evidence from randomized controlled trials (RCTs) on interventions examining gender equity in workplace or volunteer settings. An additional aim was to determine whether interventions considered intersection of gender and other variables, including PROGRESS-Plus equity variables (e.g., race/ethnicity). METHODS: Scoping review conducted using the JBI guide. Literature was searched in MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, ERIC, Index to Legal Periodicals and Books, PAIS Index, Policy Index File, and the Canadian Business & Current Affairs Database from inception to May 9, 2022, with an updated search on October 17, 2022. Results were reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension to scoping reviews (PRISMA-ScR), Sex and Gender Equity in Research (SAGER) guidance, Strengthening the Integration of Intersectionality Theory in Health Inequality Analysis (SIITHIA) checklist, and Guidance for Reporting Involvement of Patients and the Public (GRIPP) version 2 checklist. All employment or volunteer sectors settings were included. Included interventions were designed to promote workplace gender equity that targeted: (a) individuals, (b) organizations, or (c) systems. Any comparator was eligible. Outcomes measures included any gender equity related outcome, whether it was measuring intervention effectiveness (as defined by included studies) or implementation. Data analyses were descriptive in nature. As recommended in the JBI guide to scoping reviews, only high-level content analysis was conducted to categorize the interventions, which were reported using a previously published framework. RESULTS: We screened 8855 citations, 803 grey literature sources, and 663 full-text articles, resulting in 24 unique RCTs and one companion report that met inclusion criteria. Most studies (91.7%) failed to report how they established sex or gender. Twenty-three of 24 (95.8%) studies reported at least one PROGRESS-Plus variable: typically sex or gender or occupation. Two RCTs (8.3%) identified a non-binary gender identity. None of the RCTs reported on relationships between gender and other characteristics (e.g., disability, age, etc.). We identified 24 gender equity promoting interventions in the workplace that were evaluated and categorized into one or more of the following themes: (i) quantifying gender impacts; (ii) behavioural or systemic changes; (iii) career flexibility; (iv) increased visibility, recognition, and representation; (v) creating opportunities for development, mentorship, and sponsorship; and (vi) financial support. Of these interventions, 20/24 (83.3%) had positive conclusion statements for their primary outcomes (e.g., improved academic productivity, increased self-esteem) across heterogeneous outcomes. CONCLUSIONS: There is a paucity of literature on interventions to promote workplace gender equity. While some interventions elicited positive conclusions across a variety of outcomes, standardized outcome measures considering specific contexts and cultures are required. Few PROGRESS-Plus items were reported. Non-binary gender identities and issues related to intersectionality were not adequately considered. Future research should provide consistent and contemporary definitions of gender and sex. TRIAL REGISTRATION: Open Science Framework https://osf.io/x8yae .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".