A Probe into Lexical Depth: What is the Direction of Transfer for L1 Literacy and L2 Development?
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 paper examines the intersection between heritage language (HL) learning and the development of English and Farsi deep lexical knowledge. The study compares two groups of Farsi-English bilingual children with different HL educational backgrounds and a group of English-only children by testing their paradigmatic-syntagmatic knowledge of words. A statistical analysis of the children's deep lexical knowledge was conducted in light of their HL literacy experience, second language (English) schooling, and length of residence. The findings revealed that longer length of residence and L2 schooling correlates with better performance on the L2 measures of lexical depth, whereas longer residence in the home country and first language (L1) formal schooling do not correlate with better performance on the Farsi measures. The study concluded that, in the long term, the learning of a heritage language, in combination with L2 academic instruction is more effective to the cross-lingual transfer of academic skills.
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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 | 0.001 | 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 | 0.000 |
| 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