L'ACQUISITION DES CATÉGORIES FONCTIONNELLES: ÉTUDE COMPARATIVE DU DÉVELOPPEMENT DU DP FRANÇAIS CHEZ DES ENFANTS ET DES APPRENANTS ADULTES [THE ACQUISITION OF FUNCTIONAL CATEGORIES: COMPARATIVE STUDY OF THE DEVELOPMENT OF THE FRENCH DP IN CHILDREN AND ADULT LEARNERS]
Bibliographic record
Abstract
L'ACQUISITION DES CATÉGORIES FONCTIONNELLES: ÉTUDE COMPARATIVE DU DÉVELOPPEMENT DU DP FRANÇAIS CHEZ DES ENFANTS ET DES APPRENANTS ADULTES [THE ACQUISITION OF FUNCTIONAL CATEGORIES: COMPARATIVE STUDY OF THE DEVELOPMENT OF THE FRENCH DP IN CHILDREN AND ADULT LEARNERS]. Jonas Granfeldt. Lund: Institute d'Études Romanes de Lund, Université de Lund, 2003. Pp. 268. This doctoral dissertation constitutes an excellent example of how linguistic theory can contribute to the formulation of testable hypotheses about the nature of language acquisition. Taking as a point of departure Chomsky's Principles and Parameters model and the Minimalist Program, the author carries out a careful and detailed analysis of the status and development of the Determiner Phrase (DP) in two different sets of data: (a) bilingual (French-Swedish) first language (L1) developmental data produced by three children, and (b) second language (L2) French developmental data produced by eight Swedish adult speakers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".