Understanding individual variation in levels of second language attainment through the lens of critical period mechanisms
Bibliographic record
Abstract
Mayberry and Kluender (2017) present an important and compelling argument that in order to understand critical periods (CPs) in language acquisition, it is essential to disentangle studies of late first language (L1) acquisition from those of second language (L2) acquisition. Their primary thesis is that timely exposure to an L1 is crucial for establishing language circuitry, thus providing a foundation on which an L2 can build. They note that while there is considerable evidence of interference from the L1 on acquisition of the L2 – especially in late L2 learners (as in our work on cascading influences on phonetic category learning and visual language discrimination, e.g., Werker & Hensch, 2015 and Weikum, Vouloumanos, Navarra, Soto-Faraco, Sebastián-Gallés & Werker, 2013, respectively) – there are other examples of ways in which the L1 can scaffold L2 acquisition. Mayberry and Kluender take this evidence of L1 scaffolding L2 as undermining the value of considering CPs as useful in understanding L2 acquisition.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".