Examining the Effects of Policies on the Delivery of Shelter Services to Women Who Have Experienced Intimate Partner Violence
Bibliographic record
Abstract
Problem: Shelters for abused women function within a broad context that includes intersecting social structures, policies and resources, which may constrain and limit the options available to abused women and tacitly reinforce the cycle of abuse.\nMethod: This feminist, qualitative study drew on in-depth interviews and focus groups conducted with 37 staff and 4 executive directors from 4 shelters in Ontario, Canada, along with a critical discourse analysis of salient policy texts in order to explore how salient policies and structures shape shelter service delivery and may indirectly contribute to the health and quality of life of women who access services. Together, the interviews and critical discourse analysis formed an integrated analysis of the dialectic between policy as written and enacted.\nFindings: The study findings illuminate the complexity of the system and its impact on women, shelters and the community, and highlight how specific types of social policies (particularly those related to social housing, child welfare, and income assistance) and various system structures, shape the day to day reality of shelter service delivery and impact outcomes for abused women and their children. Collectively, these findings reflect a general lack of understanding about intimate partner violence that creates monumental barriers and obstacles for shelters in delivering their services. These findings offer direction regarding where these policies could be improved, and provide a basis for shelters, policy makers, advocates, and the community to strengthen current services and policies, potentially enhancing outcomes for women.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".