Crosslinguistic influences and L3/Ln teaching
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
Abstract This study set out to investigate the potential crosslinguistic influence (CLI) of related and unrelated languages on written production errors of learners of a third (L3) or additional language (Ln). Using texts written by L1 French intermediate (B1) adult learners of Ln Catalan (French-English-Catalan [ n = 9], French-Romance languages-English-Catalan [ n = 23], French-Spanish-Catalan [ n = 9]) in a standardized exam of Catalan, the analysis used different perspectives: The linguistic aspects of errors (orthographic, morphological, syntactic and semantic), the modification types (overinclusion, omission, misordering, misselection), the intralinguistic causes and interlinguistic influences ( Corder 1971 ; Ellis 2008 ; James 1998 , 2013 ). Results show that the nature of errors in writing varies for all three paths. Pedagogical implications for supporting L1 French learners at this proficiency level 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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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