Addressing gender-based violence in Saskatchewan through second-stage housing: an overview of research and setting new directions
Bibliographic record
Abstract
Saskatchewan, Canada, has some of the highest rates of gender-based violence (GBV) in Canada, with statistics double the national average. The government of Saskatchewan does not substantively fund second-stage housing – a key mitigating solution to GBV. Nor does the province have a related action plan to reduce this violence and enhance the safety of women, gender non-conforming people, and children who are disproportionally targeted by GBV. This article demonstrates the outcomes of a knowledge synthesis on the intersection of GBV and second-stage housing across Canada. This research used an intersectional feminist approach to guide a literature review and NVivo analysis. This article’s results section demonstrates the importance of second-stage housing as it relates to the mitigation of GBV. The discussion section offers various recommendations collected across Canada that can be used in Saskatchewan to bolster the existing non-profit sector that supports victims and survivors of GBV through enhanced public funding and related supports from the provincial and federal governments. The article concludes by identifying three viable and urgent areas for future research: first, investigate the potential correlation between GBV rates and second-stage housing to examine whether support for second-stage funding impacts GBV rates. Second, identify and develop alternative assessment and evaluation metrics that shift quantitative reporting standards to qualitative understandings of success. Third, examine the interconnection between settler colonization and GBV that disproportionality targets Indigenous women through strengths-based, decolonial, Indigenous-led frameworks that are culturally appropriate and responsive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".