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 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".