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Record W2132608588

An Analysis of the Discourse Function of Saulteaux/mi-/ As Exemplified In A Traditional Cote First Nation Teaching Text

2012· dissertation· en· W2132608588 on OpenAlexaboutno aff
Lorena Lynn Cote

Bibliographic record

VenueoURspace (University of Regina) · 2012
Typedissertation
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsFunction (biology)Discourse analysisLinguisticsSociologyPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This thesis has a three-fold purpose. First it presents a Saulteaux narrative collected from a Saskatchewan reserve, Cote First Nation, transcribed, translated and analyzed linguistically. Saulteaux, the Plains dialect of Ojibwe, is spoken in the southern half of Saskatchewan and in Manitoba. The dialect studied in this thesis is the dialect that is spoken in the Kamsack area. Second, the thesis focuses on the use and function of the discourse particle /mi-/ in Saulteaux text structure. Following an introduction to the main thesis topic, a cross-dialectal survey of this discourse particle in Ojibwe, both its morphosyntactic form and word order, sets the background for a discussion of the form, function and occurrence of /mi-/ in the Saulteaux dialect of Cote First Nation. Third, the linguistic analysis is followed by a lesson plan and discussion of the means and importance for teaching this and other discourse particles and structures of the Saulteaux language in its basic communicative context. This is provided specifically for speakers of Saulteaux and others interested in teaching and preserving the language. This thesis will provide materials that can be utilized in teaching both children and adults the Saulteaux language along with the history, beliefs, traditions and customs of the Saulteaux people through traditional narratives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.028
GPT teacher head0.280
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueoURspace (University of Regina)Same topicLinguistic Variation and MorphologyFrench-language works237,207