« Prendre soin » des participants lors d’entretiens réalisés en contexte de recherches sensibles
Bibliographic record
Abstract
Ce texte présente une réflexion sur le thème des recherches sensibles en gestion des ressources humaines. Prenant appui sur trois projets de recherche réalisés auprès de personnes vulnérables, il rend compte des défis méthodologiques et des enjeux éthiques qu’impliquent des entretiens auprès de cette population. À l’aide du journal de bord, cet article propose un exercice réflexif qui met en exergue la nécessaire adaptation de l’instrumentation de recherche et de l’approche idoine afin de « prendre soin » des participants et de leur laisser un espace de parole. L’article illustre également la richesse du journal de bord pour nourrir la réflexivité du chercheur sur sa pratique et sur lui-même, notamment en contexte de recherche sensible où il doit prendre conscience de sa propre vulnérabilité.
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 | 0.095 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".