Late-L2 increased reliance on L1 neurocognitive substrates: A comment on Babcock, Stowe, Maloof, Brovetto & Ullman (2012)
Bibliographic record
Abstract
Babcok et al. (2012) claim that Paradis (1994, 2004, 2009) argues that the reliance of late L2 learners on L1 neurocognitive mechanisms increases over time across both lexical and grammatical functions, namely for lexical items as well as rule-governed grammatical procedures, when in fact one can find repeated statements to the contrary in the very publications cited by the authors. Actually, Paradis’ main contention over the past 20 years has been that, contrary to grammatical functions, lexical items (as meaning–form relationships) are always of the same nature in L1 and L2 (hence stored declaratively). Thus in L2, only the neurocognitive mechanisms on which aspects of the grammar depend change over time. Consequently, the finding that length of residence (like age of arrival) influences the mechanisms underlying regular (composed), but not irregular (stored) verb forms, is compatible with Paradis’ views, in contradiction to what Babcock et al. are also suggesting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".