Bibliographic record
Abstract
This paper proposes a distinct approach to local binding effects for reflexives and pronominals in English whereby the nature of local binding domains is a by-product of the incremental interpretation of syntactic derivations (Uriageraka 1999, Chomsky 2000, 2001), emphasizing the role of the Conceptual /Intentional interface and the computational system (i.e. bare output conditions) in shaping general principles of grammars. A significant development of the Minimalist framework is the proposal that derivations operate through phases or multiple spell outs, which allows to reduce the strict cyclicity of derivations, and related locality effects of movement, to interface (bare output) conditions and economy conditions. In this paper I propose that incremental interpretation can further capture local binding domains effects of conditions A and B of Chomsky's (1981, 1986) Binding Theory. Basically, local binding domains are shown to correspond to accessible phase domains. Our proposal hence contrasts with standard analyses (e.g. Reinhart and Reuland 1993, Pollard and Sag 1992) that define co-argumenthood as the core factor from which binding conditions are developed. Our proposal also provides a new perspective on the core contrasts between A-chain and A-bar chain w.r.t. binding and scope reconstruction effects and argues that checking of the uninterpretable feature Case is what defines potential phase domains.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".