Bibliographic record
Abstract
Chomsky’s Theory of Universal Grammar was proposed in response to “the logical problem of language acquisition”, that is, how children come to acquire L1with ease and complete success despite the insufficiency of the L1 stimulus. Chomsky attributes the phenomenon to the Language Acquisition Device or UG inherited by human brain. Since “the logical problem” exists in SLA. What is the role of LAD or UG in SLA? Or, is UG accessible to L2 learners? This is a question that has attracted SLA researchers since the establishment of UG theory. This paper gives some own analysis of one of the most influential theory of UG accessibility—Fundamental Difference Hypothesis, which belongs to the no-access views and points out its weakness by discussing its theoretical explanation as well as the supporting evidence. To be more specific, this paper will discuss mainly 2 points, one is the nine fundamental characters of foreign language learning and the other is its theoretical explanation related to the Critical Period Hypothesis.
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.
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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.035 |
| Scholarly communication | 0.003 | 0.012 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 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".