Bibliographic record
Abstract
Recent work showed that infants recognize and store function words starting from the age of 6-8 months. Using a visual fixation procedure, the present study tested whether French-learning 14-month-olds have the knowledge of syntactic categories of determiners and pronouns, respectively, and whether they can use these function words for categorizing novel words to nouns and verbs. The prosodic characteristics of novel words stimuli for noun versus verb uses were balanced. The only distinguishing cue was the preceding determiners versus subject pronouns, the former being the most common for nouns and the latter the most common for verbs, i.e., Det + Noun, Pron + Verb. We expected that noun categorization may be easier than verb categorization because the co-occurrence of determiners with nouns is more consistent than that of subject pronouns with verbs in French. The results showed that infants grouped the individual determiners as one common class, and that they appeared to use the determiners to categorize novel words into nouns. However, we found no evidence of verb categorization. Unlike determiners, pronouns were not perceived as a common syntactic class.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".