Recherche collaborative
Bibliographic record
Abstract
Dans le cadre de l’ACFAS 2018, une communication portant sur les défis de la recherche collaborative de deux doctorantes et deux étudiantes à la maîtrise a été présentée. Dans la perspective qui avait animé ce dernier colloque, nous avons été sollicitées pour écrire un article permettant de témoigner de ces différentes expériences de chercheuses en herbe et de les mettre en dialogue avec le point de vue de chercheurs expérimentés afin d’en dégager des défis important pour tout chercheur s’engageant dans la voie de la recherche collaborative. Ce sont ces défis à relever dont il sera question dans cet article.
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 | 0.035 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.024 | 0.018 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.190 | 0.093 |
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".