Relocating queer: Comparing suburban LGBTQ2S activisms on Vancouver’s periphery
Bibliographic record
Abstract
Scholarly understandings of LGBTQ2S activist geographies are largely informed by a metronormative analytical lens that inadequately captures the shifting landscapes of sexual diversity in Canadian city-regions. The gap between the available services in peripheral municipalities and the rising demand from their growing LGBTQ2S populations has mobilised fractured groups of activists to lobby for policy, programming and service changes. This paper examines sexual politics in suburban civil society, focusing on the grassroots organising of not-for-profit activist groups as they interact with local government outside of the electoral process. It compares LGBTQ2S activist practices in two neighbouring, although differently sized and demographically divergent, peripheral municipalities in the Vancouver city-region: Surrey and New Westminster. A comparative case study approach reveals how LGBTQ2S activists work through variations in suburban political opportunity structures, resource landscapes and inter-organisational relations resulting in differential practices of mobilisation and collective action. In contrast with an urban legacy of insurgent practices of LGBTQ2S resistance, suburban LGBTQ2S activisms primarily centre on enactments of local resourcefulness, community resilience and institutional reworking within more dispersed resource landscapes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".