Exploring Equity, Diversity, and Inclusion in Domestic Violence Service Provision
Bibliographic record
Abstract
Background: The experiences of domestic violence survivors are unique, varied, and complex, and services for those seeking support must be responsive to these diverse needs. Methods: To understand equity, diversity, and inclusivity within domestic violence service provision, surveys were completed by 70 professionals belonging to a local domestic violence collective. Results: Using an intersectional lens, thematic analysis of survey data revealed a gap in the literature specific to equity in service delivery and limited understanding and provision of equitable, diverse, and inclusive services. Barriers to inclusive service delivery included a lack of cultural considerations and cultural competency while proposed solutions to barriers identified the need for ongoing cultural competence education and training, expanded partnerships, and refined agency policies and procedures. Conclusion: Future studies should explore the impact of implementing sector and system level changes on those who provide and receive DV services while examining the role of cultural humility, safety, and ethical space within the DV environment.
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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 | 0.039 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.032 |
| Research integrity | 0.001 | 0.003 |
| 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".