Bibliographic record
Abstract
Cet article reexamine le concept de reseau social utilise en sociolinguistique variationniste en analysant le role que jouent divers domaines d'affiliation lies aux liens forts et aux liens faibles a Pinterieur et a l'exterieurde la communaute dans la variation morphosyntaxique dans les expressions en tete des propositions adverbiales du francais acadien du nord-est du Nouveau-Brunswick (Canada).D'apres les resultats d'analyses de type regie variable, le facteur reseau social est en mesure de predire l'emploi des formes traditionnelles comme que, quand que et si que de maniere plus stable que tout autre facteur extralinguistique, incluant la classe sociale.L'analyse des correspondances est utilisee pour operationnahser le facteur reseau social a partir des affiliations des sujets dans les domaines d'affiliation.Cette etude suggere que, dans l'explication de la variation sociolinguistique, les liens faibles meritent un examen plus approfondi et que les statistiques multivariees sont un outil des plus appropries pour ce genre d'etude.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.383 | 0.196 |
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; the direct Gemma label and the distilled Codex classifier 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".