On the interpretation of long-distance agreement in Border Lakes Ojibwe
Bibliographic record
Abstract
The aim of this article is to show that long-distance agreement (LDA) in Border Lakes Ojibwe (Central Algonquian) correlates not with topicality, as claimed in past literature, but with evidentiality (direct evidence), a finding that adds to the set of existing evidential extensions of non-evidential categories (e.g., the perfect in Georgian, participles in Lithuanian, the conditional in French) and bolsters the view that verbal agreement can also correlate with special semantics. Another important observation introduced in this article is that LDA in Ojibwe typically occurs in contexts involving verbs of perception and cognition known as transitive animate. Based on these observations, we propose that these verbs are associated with a set of ϕ-features on matrix v, while selecting an evidential feature. The latter is associated with an extended projection principle (EPP) property, which allows the embedded external or internal argument to raise to the specifier of embedded C. Finally, we show that LDA in Border Lakes Ojibwe has epistemic extensions, which have to do with the speaker’s probability and commitment towards information expressed. In this connection, we also propose that the evidential effect exhibited by LDA in Border Lakes Ojibwe is of the epistemic, rather than the illocutionary type.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".