Beyond identity management: proactive strategies of LG employees against workplace heterosexism in China
Bibliographic record
Abstract
Purpose This study investigates proactive change-oriented behaviors among lesbian and gay (LG) employees who confront workplace heterosexism (Study 1). By integrating institutional change theory and the theory of reasoned action, the research demonstrates that institutional contradictions – stemming from direct and indirect experiences of heterosexism – trigger intentions toward change. These intentions subsequently mediate the relationship between the institutional contradictions experienced and the employees’ proactive, change-oriented behaviors (Study 2). Design/methodology/approach Study 1 involved semi-structured interviews with 65 LG employees, followed by factor analyses conducted on two independent samples. In Study 2, the proposed hypotheses were further tested using a larger independent sample (N = 840). Findings Study 1 yielded a robust two-factor scale of change-oriented behaviors. Study 2 further confirmed that experiences of institutional contradictions related to direct and indirect heterosexism stimulate intentions to change, mediating the relationship between these contradictions and proactive behaviors. Moreover, continuance commitment moderates these effects by dampening change intentions in response to indirect heterosexism, while simultaneously enhancing overt voice behaviors when change intentions are present. Originality/value Departing from traditional identity management strategies, our research highlights the use of both overt voice and subtle change-oriented behaviors to challenge discriminatory practices. Additionally, our findings advance the understanding of micro-level institutional change processes and provide practical insights for fostering more inclusive workplace environments.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".