Contribution à une réflexion critique sur les humanités numériques : le cas d’une recherche compréhensive sur les processus créatifs d’adolescents
Bibliographic record
Abstract
Les humanites numeriques (HN) suscitent des critiques de la part de chercheurs, qui craignent de voir les sciences sociales placees sous l’emprise d’imperatifs strictement lucratifs. Les HN ont peu fait l’objet de critiques du point de vue de la recherche comprehensive , qui questionne le pourquoi des actions des individus. Cet article propose une critique des HN, fondee sur le recit d’une recherche dont l’objectif etait de comprendre les raisons orientant les processus creatifs d’adolescents ayant publie dans YouTube une video sur le theme de la cyberintimidation. Le deroulement de sa phase de collecte de donnees ainsi que les defis l’ayant marque sont rapportes en details. Les strategies de recrutement de participants qui ont ete mises en œuvre pour relever ces defis sont ensuite presentees. L’article vise a montrer les limites des promesses des HN pour la recherche comprehensive ainsi que l’importance de « l’imagination methodologique » du chercheur pour la mise a bien de ses travaux.
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 | 0.037 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.048 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".