Ethnographie et théorie de la description – La construction des données sociologiques
Bibliographic record
Abstract
Peut-on concilier l’approche ethnographique et les visées scientifiques en sciences sociales ? À partir d’exemples de travail de description et de réflexions méthodologiques que l’on peut en tirer, nous voulons montrer la nécessité de reconsidérer la conceptualisation des phases de la démarche ethnographique allant de l’heuristique de la découverte à la construction d’un objet de connaissance transmissible explicitement. Cet exercice de conceptualisation de certains aspects du travail ethnographique permettra d’avancer la proposition suivante : le projet d’une théorie de la description du social dans ses formulations anciennes ou plus récentes, loin d’être un carcan pour l’approche ethnographique, serait une voie privilégiée pour inscrire cette démarche dans une visée scientifique. Plus encore, l’approche ethnographique pourrait bien être une contribution significative aux sciences sociales dont la scientificité demeure problématique.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.051 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".