Bibliographic record
Abstract
Social movements, and in particular feminist movements, have been marked by conflicting identities that have relegated to the margins minoritized activists. Recent work on LGBTQ movements across Europe and North America have further shed light on the ways in which processes of marginalization, such as sexism, cisgenderism, and racism, have shaped these movements, thereby pointing to the whiteness of LGBTQ social movement organizing. Quebec’s LGBTQ movement offers an interesting case study wherein whiteness and racialization have remained overlooked by academics. Building on the concept of intersectional praxis, this chapter aims to further understand how activists and organizations respond to whiteness within Quebec’s LGBTQ movement. In-depth interviews conducted with 27 LGBTQ activists reveal that intersectional praxis unfolds in two ways. On the one hand, intersectional praxis from within, wherein existing organizations build on intersectionality to include racialized activists, actually works at maintaining whiteness by reducing racialized activists to their race and reproducing tokenism. On the other hand, intersectional praxis at the margins, which consists of organizing around separate identities and outside existing organizations, works at challenging whiteness by creating safer spaces that facilitate social movement participation and render visible non-white LGBTQ identities within and outside the movement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.062 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".