Itinéraire ethnographique d’une doctorante : dialogue autour de la (dé)construction de l’objet de recherche
Bibliographic record
Abstract
Cet article rend compte des manières dont la vigilance ethnographique a permis de \ncomposer avec les obstacles qu’une doctorante – ethnographe en herbe – a rencontrés \ndans la construction de son objet de recherche. La réflexion proposée ici s’appuie ainsi \nsur sa recherche doctorale qui porte sur les processus relationnels mobilisés par des \nélèves de milieux défavorisés pour « s’en sortir ». La trame narrative prend la forme \nd’une conversation entre la doctorante et sa codirectrice et permet de retracer les \ndifférentes épreuves, hésitations et négociations qui se sont soldées en transformations \nsuccessives de l’objet ethnographique. Nous montrerons ainsi qu’au fil de rencontres, la \nvigilance ethnographique permet de se détacher des cadres formels prescrits, théoriques \net méthodologiques, et d’exploiter les contraintes du terrain en ressources au profit de la \nconstruction ancrée de l’objet.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".