Perceived Gender Discrimination and Women’s Subjective Career Success: The Moderating Role of Career Anchors
Bibliographic record
Abstract
Subjective career success reflects an individual’s internal apprehension and evaluation of his or her career, across any dimensions that are perceived relevant by the individual. It has beneficial consequences on several individual and organizational outcomes, such as job performance, employee commitment, occupational retention as well as organizational retention. Given the pervasive result that women are subjected to gender discrimination in the workplace, we first wanted to check whether the level of perceived discrimination they report having faced is related to their subjective career success. We also wanted to check whether individual priorities, as evidenced in the concept of career anchor, have an influence on the relationship between perceived discrimination and career success. Using a sample of 300 women employees working in a large French company, we therefore investigated the relationship between perceived gender discrimination, subjective career success and career anchors. We found that perceived gender discrimination was negatively related to subjective career success overall. However, the relationship between the two variables was moderated by career anchors. Some anchors (i.e. managerial, technical and lifestyle) enhanced the impact of perceived gender discrimination, while other anchors (i.e. security and autonomy) lessened it. Our results show how individual expectations, reflected in the notion of career anchor, have an influence on how the work environment is interpreted. In addition, they provide a potential explanation for the apparently contradictory findings of the literature on gender and career success. Finally, our results suggest that organizations should pay special attention not only to the work experiences of women who aspire to move up the hierarchy, but also to the women who aspire to achieve a high level of competency at their job, or seek balance between their work life and their home life.
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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 | 0.002 | 0.007 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".