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
There is presently a lively debate in second language (L2) acquisition research as to whether (adult) learners can acquire linguistic phenomena located at the interface between syntax and other modules, such as semantics, pragmatics, and lexical semantics, in contrast to phenomena that are purely syntactic in nature. For some researchers, the interface is precisely the place where fossilization occurs and the source of nonconvergence in L2 speakers. In this article we focus on the acquisition of the morphosyntax-semantics interface by examining the acquisition of mood in Spanish relative clauses by native speakers (NSs) of English. In particular, we focus on the contrast illustrated by Busco unas tijeras que corten “I am looking for scissors that cut- subj ” versus Busco unas tijeras que cortan “I am looking for scissors that cut- ind .” When the indicative is used, there is a specific pair of scissors that the speaker is looking for. With the subjunctive, any pair of scissors will do, as long as it satisfies the condition expressed by the relative clause; the determiner phrase is nonspecific. In other words, we are dealing not with ungrammaticality, as both moods are possible in these contexts, but rather with differences in interpretation. General results showed that the learners could appropriately select the expected mood. We also saw that performance was not uniform across the various conditions tested. However, variability is not solely a product of L2 acquisition; we show it can be found in NSs as well.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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