Activism, intersectionality, and community psychology: The way in which Black Lives Matter Toronto helps us the examine white supremacy in Canada's LGBTQ community
Bibliographic record
Abstract
Black Lives Matter's Toronto chapter protested at the city's 2016 LGBTQ Pride parade to make pointed demands for more funding, access to space, and the removal of police presence at future pride celebrations. Their protest led to polarizing discussions about Black Lives Matter's involvement in the community and white supremacy in the LGBTQ community, with rhetoric that attempted to separate blackness from queerness and transness. Drawing from the protest and its tumultuous aftermath and from literature on Black Lives Matter and the LGBTQ movement, this paper explores points of tension and intersection between the Black Lives Matter movement and the LGBTQ movement. It then examines critical race theory, queer theory, transgender studies, and intersectionality as theoretical lenses for Black Lives Matter and LGBTQ movements. Implications for community psychology praxis with Black Lives Matter and LGBTQ movements are outlined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.043 | 0.056 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".