From Faible to Strong: How Does Their Vocabulary Grow?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study drew on an 80,000-word corpus consisting of narrative texts produced in response to picture prompts by 210 beginner-level francophone learners of English (11-12-year-olds). The unique feature of the corpus is its longitudinal character: The samples were collected at four 100-hour intervals of intensive language instruction, during which time students made considerable progress in listening and speaking. However, analysis of these staged sub-corpora using Laufer and Nation's 1995 Lexical Frequency Profile did not identify the expected increase in use of less frequent words. Further analyses using three measures available at (a Greco-Latin cognate index, a count of word families, and a types-per-family ratio) showed that although the learners continued to use large proportions of frequent words, their productive vocabulary featured fewer French cognates, a greater variety of frequent words, and more morphologically developed forms. Implications for frequency-based vocabulary acquisition research and vocabulary teaching are discussed.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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 it