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
There are a number of phenomena where an apparent animacy requirement exceptionally admits some inanimate causers as felicitous. In this paper I argue that these should be explained not by a syntactically visible animacy feature but rather by a “what-can-cause-what” approach. In this kind of approach, judgments of felicity occur exactly when, conceptually speaking, the causing eventuality is able to cause the effect eventuality. I show how a what-can-cause-what approach for futurates and have causatives explains their felicitous inanimate causer exceptions, as well as other behavior such as interactions with aspect, using a novel notion of “dispositional causation”. The dispositions in question include both intentions of animate entities and physical tendencies. Dispositions, as well as the holders of dispositions and the causal relation, can either be represented explicitly in the syntactic structure, or can be merely implicitly available, through the accommodation of a conceptual model of dispositional structure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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 it