Bibliographic record
Abstract
Abstract Bound variable anaphora(BVA) is the term given to contexts where a pronominal anaphor functions like a logical variable in that its interpretation co‐varies with the value assigned to its antecedent in a given universe of discourse. For example, in a math class with four girls (Alice, Beth, Carol, and Diane) the interpretation of the pronounshein the English sentenceEvery girl in math hopes thatshewill be an astronautvaries according to which girl is picked out. For such a sentence to be evaluated as true it must be the case that each substitution of the pronoun for a constant yields a true proposition: Alice hopes that Alice will be an astronaut, Beth hopes that Beth will be an astronaut, and so on. Such sentences can be rendered by logical formulas such as [allx, λx[girl‐in‐math(x)] λx[xhopes thatxwill be an astronaut]. The study of BVA has figured prominently in modern studies of grammar, and has proven to be an important testing ground for formal theories of syntax and semantics. In this chapter, we focus on the syntax of BVA. After establishing that the necessary and sufficient conditions for BVA represent a convergence of semantic and syntactic properties (section 1), we examine the distribution of bound variables in A‐binding and A′‐binding contexts (section 2). We then turn to the question of the form of (A‐bound and A′‐bound) BVAs (section 3), focusing on whether they can surface as reflexives, (overt or covert) pronouns, copy‐anaphors, unspecified bindable expressions (UBEs), or indexicals. After considering whether the internal syntax of bound variables is uniform (section 4), we attend to their semantic type (section 5). We conclude with a retrospective assessment of how analyses of BVA have developed over time, and speculate about future prospects (section 6).
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".