Bibliographic record
Abstract
L’étude des mythes est un champ négligé en sociologie. La réflexion sur ce thème a nourri une prestigieuse tradition de recherche en anthropologie. Mais l’analyse des mythes dans les sociétés contemporaines est surtout le fait de littéraires et de sémiologues. Il y a ici, du point de vue de la sociologie, une carence à combler. Le présent article s’inscrit dans cet esprit. Il expose une démarche sociologique d’analyse théorique et empirique des mythes – plus précisément des mythes sociaux – comme composante des imaginaires collectifs et comme mécanisme universel. L’article soumet une définition du mythe qui fait ressortir son caractère distinctif parmi l’ensemble des représentations collectives, il rappelle les fonctions essentielles qu’il remplit dans toute société, il introduit de nouveaux concepts et propose un cadre analytique pour rendre compte de l’émergence, de la reproduction et du déclin des mythes.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".