A Conceptual Exploration of Endometriosis Disclosure and its Impact of on Women’s Career Progression
Bibliographic record
Abstract
Endometriosis is a debilitating disease that affects approximately ten percent of reproductive-aged women. However, its specific ramifications on women’s professional development and career trajectory remains inadequately understood. This conceptual paper explores the challenges women who disclose their endometriosis condition face in the workplace, examining the impact of disclosure on career progression. Drawing from stigma management theory and intersectionality theory, we explore how supervisors’ stereotypes and limited understanding of endometriosis contribute to negative perceptions, hindering women’s career progression. We also introduce downplaying behavior, whereby women may engage in behaviors that de-emphasize the symptoms to reduce the negative perceptions. Though this behavior may make women suffer in silence, it is proposed to circumvent challenges surrounding career progression. Our research advances discussions on gender, health, and workplace dynamics in the hopes of contributing to developing more inclusive and supportive work environments for women facing health-related challenges like endometriosis. A discussion and implications are outlined.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".