Zeziikizit Kchinchinaabe: A Relational Understanding of Anishinaabemowin History
Bibliographic record
Abstract
abstract: Relationships are the heart of Anishinaabeg culture and language. This research proposes understanding Anishinaabemowin, the language of Ojibwe, Ottawa, and Potawatomi peoples, as a living, historical, and spiritual member of the cultural community. As a community member, the language is the Oldest Elder. This understanding provides a relational lens through which one can understand language history from an Indigenous perspective. Recent scholarship on Indigenous languages often focuses on the boarding school experiences or shapes the narrative in terms of language loss. A relational understanding explores the language in terms of connections. This dissertation argues that the strength of language programs is dependent on the strength of reciprocal relationships between the individuals and institutions involved. This research examines the history of Anishinaabemowin classes and programs at three higher educational institutions: Bemidji State University, University of Michigan, and Central Michigan University. At each institution, the advocates and allies of Oldest Elder fought and struggled to carve space for American Indian people and the language. Key relationships between advocates and allies in the American Indian and academic communities found ways to bring Oldest Elder into the classroom. When the relationships were healthy, Oldest Elder thrived, but when the relationships shifted or weakened, so did Oldest Elder's presence. This dissertation offers a construct for understanding Indigenous language efforts that can be utilized by others engaged in language revitalization. The narrative of Oldest Elder shifts the conversation from one of loss to one of possibilities and responsibilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".