Bibliographic record
Abstract
In Blackfoot, a Plains Algonquian language spoken in Alberta, Canada, and Montana, USA, sentience, rather than telicity, is a primary determinant of argument structure. Subjects of transitive verbs, non-core objects of transitive verbs (benefactives, malefactives, sources, etc.), and primary objects of ditransitive verbs are all subject to a strict sentience requirement. This chapter follows Ritter and Wiltschko (2015) in assuming that the strict sentience requirements on argument structure are part of the grammar (i.e. part of the “narrow syntax”) of Blackfoot, and formalizes sentience as a feature that is subject to selection, a feature-checking operation, much like AGREE. This proposal correctly predicts that (a) not only agents but also causers must be sentient in Blackfoot; (b) sentient objects (not bounded ones) serve as both initiators and delimiters of events; (c) like event types, nominal types are distinguished by sentience, rather than boundedness; and (d) eventiveness is correlated with sentience, rather than dynamicity.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".