“If you don’t stop the cycle somewhere, it just keeps going”: Resilience in the context of structural violence and gender-based violence in rural Ontario
Bibliographic record
Abstract
Bolstering women's resilience in the context of gender-based violence (GBV) requires attention to structural conditions needed to support women to thrive, particularly in rural communities. This cross-sectional study explored how resilience was influenced by structural violence in rural Ontario among women experiencing GBV (n = 14) and service providers in the GBV sector (n = 12). Interviews were conducted and revealed forms of structural violence that undermine resilience for women experiencing GBV in rural communities, including 1) housing- gentrification, short-term rentals of residential properties, and long waitlists, 2) income- fighting for enough money to survive, 3) safety- abusers gaming the system, and 4) access- successes and new barriers. Structural conditions must be attended to as they are prerequisites required to build resilience.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".