Grammaticalizing the size of Situations: The case of Bulgarian
Bibliographic record
Abstract
Situation-semantics as developed by Kratzer (e.g. 1989, 2011) has proven an illuminating framework for a variety of linguistic puzzles. Semantic theories building on Kratzer-style situations have appealed to situation ‘size’ to explain phenomena such as adverbial quantification and presupposition projection (e.g. Berman 1987, Heim 1990, Elbourne 2005, among others). In this paper, we propose a novel perspective on situation size in order to account for restrictions on the interpretation of aspectual morphology, in particular as associated with ‘viewpoint aspect’ (Smith 1991/1997). While situation size has been manipulated in situation-semantics, the focus so far has been on distinguishing ‘minimal’ situations with certain properties. We argue that ‘big’ situations are also worth examining. In particular, distinctions between ‘big’ vs. ‘small’ situations are argued to provide insights into aspectual oppositions resulting in habitual/generic vs. singular/episodic/ongoing interpretations. The empirical focus is on Bulgarian constructions that integrate a particularly rich array of aspectual morphology, bringing together features from Slavic and Romance and providing an ideal vantage point from which to study constraints on aspect.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".