The first language acquisition of nominal inflection in Northern East Cree: Possessives and nouns
Bibliographic record
Abstract
This is a modified version of a 2020 dissertation, submitted by the author in 2022, featuring bookmarks within the PDF and corrected pagination. Per the author, the dissertation has otherwise not been changed. Original and full abstract can be found at http://hdl.handle.net/10125/69015. Brief abstract: "This dissertation describes the first language (L1) acquisition of nominal inflection in Northern East Cree (NEC), a member of the Cree-Innu-Naskapi dialect complex within the Algonquian language family, which is spoken in four Eeyou Istchee communities in Northern Québec. The category of nominals includes nouns, demonstratives, and pronouns, where nouns inflect with templatic morphology involving one prefix and four suffix positions. This study focuses primarily upon nouns within possessive constructions, which entail the richest range of inflectional possibilities and mark multiple inflectional features of both possessees and possessors—including grammatical animacy, obviation, and number. This is the first dedicated study of the L1 acquisition of possessive marking within a polysynthetic language, and this dissertation aims to provide findings to inform linguistic science as well as community-centered efforts in L1 development and language revitalization."
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".