Noun Categorization in Ojibwe: Gender and Classifiers
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Bibliographic record
Abstract
Ojibwe is an Algonquian language spoken around the Great Lakes region of the United States and Canada. It has grammatical gender and a classifier system, which are rare in a single language (Corbett, 1991:137; Fedden and Corbett, 2017). I provide a detailed and typologically-informed analysis of numeral and verbal classifiers in Ojibwe. Numeral classifiers can be of two types: mensural, referring to measurements, and sortal, referring to properties such as dimensionality, size, and material. It is shown that these types can be distinguished by occurring with differing forms for the numeral 'one', and sortal classifiers are vital to understanding gender assignment. Assignment is mostly straightforward, with all nouns denoting humans and animals in the ANIMATE category, and the vast majority of nouns denoting inanimates in the INANIMATE category. However, some nouns with inanimate referents are ANIMATE. Previously characterized as 'exceptions' to semantic assignment, they are motivated by compatibility with the semantics of one of these sortal classifiers, as illustrated by pairings of classifiers and nouns (1). I also discuss the role of analogical extension, dialectal variation, diachronic change and claims for an interaction of gender with the count/mass distinction. 1. a. /-aatig/ '1D, rigid', i.e. stick-like - mitig 'tree' b. /-aabiig/ '1D, flexible', i.e. string-like - zesab 'nettle' c. /-eg/ '2D, flexible', i.e. sheet-like - asekaan 'tanned hide' d. /-minag/ '3D, small, round', i.e. berry-like - miskomin 'raspberry' e. /-aabik/ 'mineral', i.e. metal, stone, glass - asin 'a stone'
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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 | 0.000 |
| 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) | 0.000 | 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