Language profiles of poor comprehenders in English and French
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
This study explored components of language comprehension (vocabulary, grammar, and higher‐level language) skills for poor comprehenders in French immersion. We identified three groups of bilingual comprehenders (poor, average, and good) based on English reading performance and compared their language comprehension skills in English L1 and French L2. We also identified and compared English skills for three groups of monolingual comprehenders from English‐stream programmes. Among both bilingual and monolingual learners, poor comprehenders performed significantly lower than good comprehenders on English vocabulary, morphological awareness, and inference. Bilingual poor comprehenders also differed from average comprehenders on English morphological awareness and inference. Similar results were found in French for the bilingual learners. Lower scores on French vocabulary and morphological awareness distinguished between bilingual poor and good comprehenders. Additionally, weaknesses in French semantics and inference distinguished between bilingual poor and good comprehenders and bilingual poor and average comprehenders. These results suggest that poor comprehenders share remarkably similar language characteristics in L1 and L2.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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