Bilingualism, Language Development, and Brain Plasticity
Bibliographic record
Abstract
This chapter distinguishes studies on the mind from studies investigating the brain. By describing linguistic, psychological, and cognitive neuroscience approaches, some aspects which have been found to be relevant for bilingualism have only been studied in linguistic terms, leaving open whether certain findings are limited to the mind level only or whether there is any correspondence on the brain level. Other aspects, well researched in linguistic or psychological studies, have not yet been taken up in neuroscientific studies, leaving the question of whether certain variables would change the results or explain variance unanswered. We then look at details of learning in the brain and in particular at brain plasticity, a lifelong available characteristic of the brain. The chapter also addresses the notion that for linguists, acquisition and learning are not the same, since context in general and factors such as input quality and quantity must be taken into account. In brain terms, there is only learning. We then discuss different factors influencing language acquisition and learning and reveal that individual differences can be found among these factors to a great extent.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".