Entre allers et retours : approches de l’anthroponymie dans les Pyrénées occidentales (xiiie-xviie siècle)
Bibliographic record
Abstract
De part et d'autre des Pyrénées occidentales, l'évolution des noms de famille témoigne entre le xiiie et le xviie siècle de circulations humaines au goutte à goutte mais persistantes en Haute-Navarre. Les riches listes nominatives permettent de poser la question de conversos cherchant à se fondre dans la population. Entre nord et sud de l'ancien royaume de Navarre, on observe le renouvellement de la noblesse, des professions, mais on constate aussi des mouvements inverses sud-nord. Les migrations des Basques catholiques deviennent sensibles après le choix du protestantisme par Jeanne d'Albret. Mais le passage constant dans le temps des éleveurs cadets du Nord suffit à expliquer ces évolutions anthroponymiques lentes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".