Co-predications and the quantificational force of summative predicates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In the literature on homogeneity, summative predicates have been described as quantifying universally over their argument’s parts in positive sentences, while being negated existentials in negative sentences. In this article, I provide a fuller picture of these predicates’ quantificational force in positive sentences through various ‘co-predications’—sentences in which two summative predicates are predicated of the same individual. In some co-predications, summative predicates are universal; in others, they are weaker, while remaining stronger than existential. In light of this new empirical paradigm, I suggest that summative predicates are lexically existential, but are exhaustified so as to exclude other same-class predicates. In addition to making this proposal, I also show that no other theory of homogeneity can capture the co-predicational paradigm.
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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 | 0.000 |
| 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) | 0.000 | 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 it