“I’m Not Thinking of It as Sexual Harassment”
Bibliographic record
Abstract
How do diverse groups of women in Canada define sexual harassment? To answer this question requires incorporating race and citizenship into the analysis of sexual harassment. The authors use data from seven focus groups of Canadian women. The white women with full citizenship rights most easily identify with existing legal understandings of sexual harassment and believe they have the right to report their harassment. For women of color and women without full citizenship rights, issues of racialized sexual harassment emerge as central factors in their harassment experience. Black women with full citizenship rights call into question whether the term sexual harassment captures their experiences. Filipinas working as live-in caregivers on limited visas demonstrate how racism and lack of citizenship changes definitions of sexual harassment. Their experiences of harassment combine elements of isolation due to their lack of citizenship, racialized sexual harassment, and abuse. The authors argue that intersectional analyses are needed to understand women’s harassment experiences and their ability to complain and seek legal recourse.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".