Far Beyond the Gay Village: LGBTQ Urbanism and Generation in Montréal’s Mile End
Bibliographic record
Abstract
Abstract Research on LGBTQ neighbourhood formation in the urban West suggests that new patterns of community and identity are reshaping the queer inner-city and its geographies. As gay village districts “decline” or are “de-gayed” and new generations “dis-identify” with the urban ideals that once informed their production, LGBTQ subcultures are producing varied alternatives in other inner-city neighbourhoods. Beyond the contours of ethno-racialization and social class, generational interpretations of LGBTQ urbanism—subcultural ideals regarding the relationship between sexual and gender identity and its expression in urban space—are central to the production of such new inner-city LGBTQ subcultural sites. This chapter provides a qualitative case study Montréal’s of Mile End, an inner-city neighbourhood that, by the early 2010s, was touted as the centre of the city’s emerging queer subculture. Drawing on a sample of young-adult (22 to 30 years) LGBTQ-identified Mile Enders (n = 40), it examines generational shifts in perceptions of sexual and gender identity, queer community and neighbourhoods. The chapter concludes with a discussion of the implications of queer Mile End for theorizing the contemporary queer inner-city.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".