Overcoming Repression: Effective Strategies of Contemporary Black Social Movements in Canada and the United States
Bibliographic record
Abstract
Although there has been an increase in Black activism after the murder of George Floyd in 2020, Black social movements continue to face obstacles. This research focuses on how pro-Black movements can overcome the repression they face to reach their goals of Black social change. Specifically, this research studies contemporary Black social movements in Canada and the United States to analyze what effective strategies are. This was examined by conducting ten qualitative, semi-structured interviews with members of contemporary Black social movements, with five being from Canada and five being from the United States. Research participants sat through interviews where conversations about their experiences with Black activism, as well as successful and unsuccessful strategies, were facilitated. This research concluded that effective strategies for Black movements to create Black social change are not heavily based on specific action strategies, such as rallies and protests, but more based on effective ways of organizing.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.034 | 0.017 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".