Au-delà de l’arc-en-ciel : parcours, trajectoires et altérités dans le Village de Montréal
Bibliographic record
Abstract
Ce mémoire de maitrise explore l’hétérogénéité et la diversité dans le Village de Montréal. Il s’intéresse à ce quartier au-delà de ce que sa vitrine commerciale laisse voir. Ses lieux de sortie et de rencontres, tout comme ses autres commerces et ses tissus résidentiel et communautaires, ne seraient pas des blocs homogènes, mais des mosaïques qui sont investies par une multitude de personnes, de groupes et de communautés. Ceux-ci, dépendamment de leurs trajectoires et de leurs parcours, ont des perceptions et des vécus forts différents les uns des autres des mêmes lieux, d’une part, et du Village dans son ensemble, d’autre part. Sur la base d’une analyse documentaire et de six (6) entrevues menées auprès de personnes qui fréquentent les milieux communautaires et activistes LGBTQ, ce mémoire révèle les multiples stratégies et manières d’occuper l’espace urbain dans le Village, et les réseaux et les lieux où s’observe cette diversité.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".