Linguistic distance and crosslinguistic influence: Commentary
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This commentary addresses three issues that arise in the context of linguistic distance and crosslinguistic differences, namely how linguistic distance is defined, how linguistic distance translates into linguistic knowledge, and what the relationship is between linguistic distance and crosslinguistic influence. As far as distance is concerned, articles in this issue differ as to whether they adopt external or internal measures of language distance, raising the question of how externally defined language relatedness translates into the internalized grammar of an individual learner. As for crosslinguistic differences, there is an assumption in some of the articles that the more different/typologically apart the languages are, the harder the second language (L2) will be to acquire and the greater the prospect of first language (L1) transfer. In contrast, several articles show that typological closeness does not necessarily facilitate acquisition, while distance does not impede it. Discrepancies and commonalities between the various approaches are discussed.
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.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it