Making Change on Gender-Based Violence: Assessing Shifting Political Opportunities in Canada
Bibliographic record
Abstract
Feminist anti-violence organizations provide much needed services and advocate for changes to culture and policy. However, their ability to continue with this work is jeopardized by fraught and changing relations with governments. This is especially the case for state-funded feminist service organizations which, through their ties to state funders, risk their ability to engage in advocacy. While scholars and activists warn of the challenges associated with state funding, situating funding relationships within particular social, historical, geographic, and political contexts can illuminate both the threats facing feminist service organizations, as well as openings in the political opportunity structure. Using the Canadian province of Ontario as a case study, this paper highlights changes to funding for anti-violence work between 1990 and 2015 and considers the implications of shifts in the funding regime. My findings indicate that while state resources for anti-violence initiatives have expanded over time in both the province of Ontario and at the federal level, neoliberal governance has altered the distribution of government funding which has contributed to heightened competition between organizations. I conclude by offering reflections on existing political opportunities for the feminist anti-violence movement in Canada.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".