Bibliographic record
Abstract
Deux procédés, ou formes de stylisation, couramment utilisés par les sociologues sont examinés : le récit (ou mise en intrigue) et le type idéal. Ces deux procédés ne sont pas propres aux sociologies dites interprétatives mais elles ont des dimensions herméneutiques. La mise en intrigue et la création d’un type idéal se font dans le prolongement des interprétations des acteurs qui mettent eux-mêmes en récit ce qui leur arrive et typifient leurs conduites. Les sociologues prennent ainsi le relais de ces premières interprétations, tout en s’en distanciant. En outre, ces deux procédés peuvent contribuer à mettre en lumière les enjeux moraux et politiques de la collectivité étudiée, ainsi que la création, la liberté et la réflexivité des acteurs, et donc à nouveau leur travail d’interprète, ce qui leur confère également un caractère herméneutique. La discussion se fait autour de quelques exemples.
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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.059 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".