Les applicatifs dans une langue à « voix inverse » : le cas de l'innu-aimun, langue algonquienne du Québec
Bibliographic record
Abstract
Innu-aimun is an Algonquian language, mostly spoken in Quebec. This language family is famous for its « direct-inverse » system, a syntactic device that can be described in terms of voice and alignment according to the respective properties of the referents that embody the semantic roles of a bivalent predicate. Because the basic function of an applicative is specifically to add a semantic role to the valency of a predicate (progressive diathesis, in Tesnière's terminology), such an operation may have morphosyntactic repercussions in these languages. This article introduces some relevant characteristics of the Innu language and presents the various applicatives found in Innu-aimun. It discusses how and why only some of them interact with alignment issues. As a conclusion, we support that Innuaimun data provide some insights for the construction of a typological concept such as "applicative".
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".