L2 ultimate attainment and the syntax-discourse interface : the acquisition of topic constructions in non-native Spanish and English
Bibliographic record
Abstract
This thesis investigates the syntax-discourse interface in adult, end state second language (L2) acquisition. Specifically, it examines topic constructions in Spanish and English, namely Clitic Left Dislocation (CLLD) and Contrastive Left Dislocation (CLD), which exhibit both syntactic and discourse level properties. In both cases, topics occur at the left periphery of clauses and reintroduce a subset of a known set previously mentioned in discourse. Sensitivity to specificity is available in Spanish but not in English. The interpretation of the topicalized element as either generic or specific depends on the presence or absence of the clitic. Data from a bidirectional study are reported in order to investigate the issue of L1 transfer as well as the question of whether acquiring a new property is easier than losing a property.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".