Synthèse de la Session Semi-plénière « Sociologie dans, depuis et sur les Outre-mers », du 6 juillet 2023, Congrès de l’Association française de sociologie, Lyon
Bibliographic record
Abstract
Lors de la semi-plénière du groupe SocioOM à l’AFS 2023, quatre chercheur·ses – Audrey Célestine, Valélia Muni-Toké, Live Yu-Sion et Marine Haddad – ont partagé leurs expériences de la sociologie dans, depuis et sur les territoires dits d’Outre-mer. Ces échanges ont mis en lumière les difficultés institutionnelles rencontrées dans des contextes où les structures académiques locales en sociologie sont souvent faibles ou absentes. Les intervenant·es ont évoqué les enjeux de la production de savoirs dans ces territoires, les tensions autour de la visibilité scientifique, ainsi que les défis méthodologiques et éthiques spécifiques à ces terrains. Trois temps ont structuré la session : expériences de terrain, enjeux de visibilité, et méthodologies, avant un échange avec le public.
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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| 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".