La documentation périodique en anthropologie : variabilité, classification et indexation
Bibliographic record
Abstract
La variabilité des périodiques en anthropologie est mise en évidence par l’analyse de 204 titres tirés du répertoire Ulrich’s. Même si 26 langues et 49 pays producteurs différents sont identifiés, il existe dans ce domaine un quasi-monopole anglo-saxon. L’hétérogénéité du contenu est déterminée par deux facteurs qui caractérisent le développement récent de l’anthropologie : l’interdisciplinarité et la multiplication des spécialités. Quatre classifications intuitives des périodiques sont évaluées et comparées à une typologie statistique. Peu de périodiques offrent à leurs lecteurs un index récapitulatif. Plusieurs des 22 index étudiés ne répondent pas aux critères de qualité proposés dans les manuels et les normes d’indexation.
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 | 0.035 | 0.111 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.042 | 0.063 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".