Learning Island-insensitivity from the input: A corpus analysis of child- and youth-directed text in Norwegian
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
Norwegian allows filler-gap dependencies into relative clauses (RCs) and embedded questions (EQs) – domains that are usually considered islands in other languages. We conducted a corpus study on youth-directed reading material to assess what direct evidence Norwegian children receive for filler-gap dependencies into islands. Results suggest that the input contains examples of filler-gap dependencies into both RCs and EQs, but the examples are significantly less frequent than long-distance filler-gap dependencies into non-island clauses. Moreover, evidence for island violations is characterized by the absence of forms that are, in principle, acceptable in the target grammar. Thus, although they encounter dependencies into islands, children must generalize beyond the fine-grained distributional characteristics of the input to acquire the full pattern of island-insensitivity in their target language. We consider how different learning models would fare on acquiring the target generalizations and speculate on how the observed distribution of acceptable filler-gap dependencies reflects the interaction of syntactic, semantic, and pragmatic conditions.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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