Bibliographic record
Abstract
While Horn (1969) proposed that [[only]](p) presupposes that the prejacent p is true, von Fintel & Iatridou (2007) showed that the expected prejacent inference is not observed when a necessity modal occurs in the scope of only: [[only]](□p) may convey that p is possible, rather than necessary. What is the mechanism behind the surprisingly weak inference? The approach in von Fintel & Iatridou 2007 is to revise the analysis of only itself to weaken its contribution. In this paper, however, we argue that Horn’s only is correct after all, and introduce a source of weakening separate from only. In particular, in von Fintel & Iatridou’s modal environment, a phonetically null operator (AT LEAST; Crnic̆ 2011, Schwarz 2005) occurs in the scope of only to weaken the presupposed prejacent. Much recent attention has been paid to covert operators which strengthen meaning, in particular a covert EXH with a meaning similar to only (e.g. Chierchia 2006, Fox 2007, Chierchia et al. 2012). A key consequence of our analysis is that natural language incorporates a covert weakening operator, as well. EARLY ACCESS
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.021 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.011 |
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".