The Importance of Accuracy in the Use of Grammatical Terms and Concepts in the Description of the Distinctive Properties of Plains Algonquian Languages
Why this work is in the frame
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Bibliographic record
Abstract
The subject of this paper was inspired by my collaboration on a project involving the long-term histories of grammatical traditions led by Dr. Philomen Probert at the University of Oxford. Owing to my interest in linguistic typology and the study of the syntax-semantics-pragmatics interface in a number of languages, – especially Native American languages, which differ in many respects from Indo-European languages, –, I have observed that some languages cannot be accurately described if we use the grammatical terms and concepts commonly applied to the analysis of extensively studied languages such as English, Spanish or French, as certain grammatical properties of one language may not be equivalent to those of another and, consequently, require a different treatment. Thus, firstly, by adopting a holistic comparative perspective deriving from all areas of grammar, I aim to reveal the distinctive features that Plains Algonquian languages such as Cheyenne / Tsėhésenėstsestȯtse (Montana and Oklahoma, USA), Blackfoot / Siksiká, Kainai, and Pikani, (Montana, USA; Alberta, Canada), Arapaho / Hinóno´eitíít (Wyoming and Oklahoma, USA), and Gros Ventre / White Clay or Atsina / Aaniiih (Montana, USA) display when compared with Indo-European languages such as English, Spanish, French or German. The subsequent examination of these data will provide examples of terms and concepts that are typically used in traditional grammatical descriptions, but that do not serve to characterize the grammar of these Native American languages accurately. Finally, I will attempt to propose alternative terms and concepts that might describe the distinctive grammatical properties exhibited by these languages more adequately.
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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 | 0.001 | 0.004 |
| 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