Navigating violence and risk: A critical discourse analysis of blind women's portrayals of self-protective measures
Bibliographic record
Abstract
Women with disabilities experience high rates of violence and harassment, yet meaningful violence prevention interventions providing the opportunity to learn how to be active agents in their own self-protection are virtually non-existent. To understand why, we draw on insights from feminist disability studies to explore some of the unexamined assumptions and discourses in gender-based violence prevention research. We then apply a feminist critical discourse analysis to focus groups with blind and partially sighted women to explore their talk about violence and self-defence to understand how they portray self-protective measures, and what practices those portrayals engender. We discerned three portrayals: self-protective measures as necessary against strangers, a delimited responsibility, and an effective means to an end. These portrayals and their subsequent practices demonstrate how the participants navigate violence while living with vision loss. We also consider the implications of our analysis for future directions in gendered violence prevention research.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".