Interroger l’itinérance : stratégies et débats de recherche
Bibliographic record
Abstract
Cet article traite des problèmes et des enjeux de recherche sur la question spécifique de l’itinérance. Les auteures démontrent, à partir d’une recension des articles scientifiques couvrant près de 20 ans, non seulement l’évolution de la recherche mais aussi et surtout les difficultés d’une recherche touchant des populations fortement stigmatisées et pour lesquelles le flou des définitions, les réalités multiples conditionnent, voire imposent des limites méthodologiques certaines. Les auteures évoquent et discutent les stratégies développées et interrogent celles-ci aussi bien sur les dimensions empiriques, théoriques qu’éthiques. Dans un contexte actuel de rareté des ressources et de remise en question de certains services, les chercheurs ne doivent pas se questionner uniquement sur la scientificité de leur recherche mais aussi sur les enjeux politiques réels associés à la production de la connaissance. Réfléchir sur les stratégies et les choix méthodologiques constitue donc, pour les auteures, une question fondamentale et incontournable.
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 | 0.187 | 0.212 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.032 | 0.036 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".