Dynamic advocacy: Legal mobilization and the pursuit of sociolegal change in Canada
Bibliographic record
Abstract
This project examines the strategic form and function of legal mobilization. The scholarship on this topic is extensive, yet it falls short of explaining how and why mobilization continues after the enactment of activist won law reform. This project remedies this by exploring the strategic determinants of post-reform sexual assault advocacy in Canada. Be it through consent workshops, online modules or informationally targeted materials, Canadian feminists have increasingly used educational strategies. Questioning how and why these strategies are used, I advance a theoretical account of activists’ opportunities and ambitions. Focusing on factors external to the activist group itself, this project proposes a theory of contemporary legal mobilization that credits the use of educational advocacy to the common pursuit of leadership amongst internally differentiated groups. The dynamics that unfold amongst activists, therefore, ground my study of legal advocacy strategy in the aftermath of legal reform.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.037 | 0.014 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".