Bibliographic record
Abstract
This paper examines the nature of finite and nonfinite main declarative sentences produced by L2 child learners. It claims that two of the main proposals on the root infinitive (RI) phenomenon, the Truncation Hypothesis (TH) and the Missing Surface Inflection Hypothesis (MSIH), are not mutually exclusive in child SLA because they are hypotheses on completely different issues. According to the TH, different roots are involved: RIs are VPs underlyingly, whereas finite clauses are IPs or CPs. The MSIH claims that L2 learners have difficulties using the exact inflectional morphology, which leads them to produce verbs with an infinitival marker or no inflection at all. These so-called default forms are finite. In principle, then, an L2 learner could project truncated structure and produce default finite forms at the same time. This possibility is investigated in longitudinal data from an English-speaking child learning German. Two complementary sets of data can be accounted for by the hypotheses. Verbs bearing a nonfinite marker are restricted to nonfinite positions, which is consistent with the TH. Bare (uninflected) forms occur in the same (finite) positions as verbs inflected for person and number, which suggests that they are finite. This finding is consistent with the MSIH.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".