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 used two methods to assess bilingual dominance in four groups of 18 Italian–English bilinguals, who were selected on the basis of age of arrival (AOA) in Canada (early: 2–13 years; late: 15–26 years) and percentage use of the first language (L1), Italian (low L1 use: 1–15%; high L1 use: 25–85%). Ratios were derived from the bilinguals' self-ratings of ability to speak and understand Italian compared to English (the “verbal” self-rating ratios) and to read and write Italian compared to English (the “written” self-rating ratios). The ratio of the mean duration of English and Italian sentences produced by each bilingual was also computed. AOA and L1 use had the same effect on the self-rating and sentence duration ratios, which were correlated. The bilinguals who arrived in Canada as young adults and continued to use Italian often were the most likely to be Italian dominant. Dominance in Italian was associated with a relatively high level of performance in Italian (assessed in a translation task) and relatively poor performance in English (assessed by measuring strength of foreign accents). Both groups of late bilinguals (late low, late high) and both groups of early bilinguals (early low, early high) were found to produce English sentences with detectable accents. However, a group of 18 bilinguals (all early bilinguals) selected from the original sample of 72 based on their dominance in English did not have detectable foreign accents. This suggested that interlingual interference effects may not be inevitable.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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