indefinite can take scope out of the ‘if ’ clause.
Bibliographic record
Abstract
The... sixth?... meeting of the McGill whenthusiasts, Winter 2008. Table 1 shows the paradigm for a couple of types of indefinite. Yanovich (2005) is investigat-ing the proper semantic representations of these indefinites (in fact, primarily just the first three, including cases where the bare interrogatives can function as indefinites). There are, in particu-lar, two types of semantic representations that he is considering: Choice functions and Hamblin indefinites. 1 The Russian-to series (1) Kto-to who-TO vošel came v into komnatu the room ‘Someone came into the room’ Yanovich shows, with the following examples, that indefinites formed with-to can take wide scope, even when they are located within a movement island. In each of the following cases, the wh-to is inside an ‘if ’ clause, but can be interpreted either inside (if> ∃) or outside ( ∃> if). He tries it for all kinds of indefinites, arguments and adjuncts. The result is the same in each case: the interrogative to nibud ’ libo ni kto ‘who ’ kto-to kto-nibud ’ kto-libo nikto čto ‘what ’ čto-to čto-nibud ’ čto-libo ničto gde ‘where ’ gde-to gde-nibud ’ gde-libo nigde kogda ‘when ’ kogda-to kogda-nibud ’ kogda-libo nikogda kak ‘how ’ kak-to kak-nibud ’ kak-libo nikak kakoj ‘what/which ’ kakoj-to kakoj-nibud ’ kakoj-libo nikakoj
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".