Navigating uncertainty, employment and women’s safety during COVID‐19: Reflections of sexual assault resistance educators
Bibliographic record
Abstract
COVID-19 affects women in ways unique to the impacts of structural inequalities related to gender, sexuality, disability, race and socioeconomic status. In this article, we reflect on our own experiences of the pandemic, as feminist students, workers and sexual assault resistance educators located in a Canadian post-secondary setting. Situating ourselves within feminist responses to sexual violence prevention, as facilitators of the Enhanced Assess, Acknowledge, and Act (EAAA) sexual assault resistance education programme for university women, we reflect on the impacts of the COVID-19 pandemic on our work as EAAA facilitators in our Canadian university. We explore the theoretical possibilities that critical disability theory and queer theory present to the EAAA programme, and argue that incorporating concepts from these frameworks will complement the goals of the EAAA programme and improve inclusivity of queer, trans and disabled participants. We conclude with a look into the future by anticipating the impacts of COVID-19 on our future work.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.055 | 0.038 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".