Domestice Violence Shelter Use Patterns in the Prairie Provinces: The Intersectionality and Complexity of Women's Help-Seeking Behaviour
Bibliographic record
Abstract
Domestic violence shelter access must be addressed within Canada as in 2013, domestic violence incidents accounted for more than a fourth of reported violent crimes and were particularly prevalent in the Prairie Provinces. Research across North America has demonstrated that domestic violence rates decline as resources become more widely available. However, only about 10% of battered women in Canada access shelter services. As a result, systemic barriers must be identified to facilitate women’s ability to escape intimate partner violence (IPV). Domestic violence policies must be better informed by women’s experiences in order to ensure that policies are properly meeting the needs of IPV victims. The Healing Journey project was a tri-provincial longitudinal study that took place across Alberta, Saskatchewan, and Manitoba. Interviews were conducted biannually between 2006 and 2009 with 665 women who had previously experienced IPV, thus constituting a total of seven waves of interviews. Quantitative data analysis consisted of primarily descriptive statistics and cross tabulations, which enabled the impact of several variables on women’s shelter use patterns to be analysed. Women’s self-reported shelter use was categorized into the respective categories: non-shelter use, and single, low, medium, and high frequency use. The major themes that emerged from the literature review informed the data analysis process. Several variables were found to influence shelter use, particularly with regards to women’s demographics, perceptions, and experiences of abuse. Findings suggest that the impact of the chosen variables on shelter use is much more complex than previous studies have identified. It is evident that intersectionality heavily influences patterns of help-seeking as the decision to leave abuse is driven by women’s unique circumstances and experiences of oppression. Accessibility of income supports, affordable housing, childcare, and employment support greatly reduce women’s likelihood of returning to abuse. As a result, the respective policies must be strengthened to ensure that women have the resources to escape domestic violence permanently. Furthermore, policies regarding upstream prevention of abuse play a critical role in addressing domestic violence. By teaching children how to develop healthy relationships, cycles of violence can be broken and future generations can develop the skills to prevent future abuse from occurring. Moving forward, public policies must be developed to address both the causes and consequences of IPV. By strengthening both responsive and preventative domestic violence policies, gender inequality and oppression that lead to IPV can be addressed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".