Gender Inequality, Stress Exposure, and Well-Being among Academic Faculty
Bibliographic record
Abstract
Gender inequalities in salary, rank and access to leadership positions characterize institutions of higher education and disadvantage women faculty. Differential exposure to noxious working conditions and restricted access to social resources may underlie these inequalities by detracting from women faculty’s well-being, thereby perpetuating the status quo. This study applies stress process theory to analyze this inequitable state of affairs, treating gender as a social status in higher education that predicts differential exposure to stressors and access to resources. Stressors and resources, in turn, predict faculty well-being. Stressors include micro-aggressions and work-life conflict, and resources include collegiality with peers and support from administrators. Survey data were collected from academic faculty at a mid-sized Western university in the U.S. Results indicate that women faculty experience micro-aggressions and work-life conflict more often than men, and report less supportive relationships with their deans. Moreover, micro-aggressions and work-life conflict are positively associated with psychological distress and job dissatisfaction, while dean support has the opposite associations. Open-ended responses supplement the quantitative findings with vivid examples of how these phenomena play out in individual faculty members’ lives. Implications for how institutions of higher education might introduce change to address these findings are discussed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".