Gikinoo'amaagowin Anishinaabeg (Teaching the Anishinaabe People)
Bibliographic record
Abstract
This thesis analyzes the roles and responsibilities of Anishinaabe Ogichidaakwe (woman warrior) using Anishinaabe and Western methodologies. As an Anishinaabekwe I use Anishinaabe language to engage in my responsibility to learn and share the language. In this thesis I move in and out of two different ways of knowing adapting to two epistemologies. While moving between Anishinaabe and Western epistemologies I located an ethical space where my spiritually connected and culturally grounded perspective is recognized. I examine and reconstruct the political/leadership, social, and spiritual roles and responsibilities of Ogichidaakwe over a critical period of change, 1632 to 1871. Anishinaabe leadership knowledge and practice experienced a shift as the Anishinaabeg community adapted to the experience of European contact. This shift is recognized after braiding together literature that is outlined in my thesis as the shift, colonial impact and absence. Of particular interest are women-based Aadizookaanag (Anishinaabe narrative with a scared being or spirit in it) and women-based Aadizookaanan (Anishinaabe narratives and ancient stories), and how these narratives are connected to Ogichidaakweg roles and responsibilities. I interconnect the Jiisikaan (shake tent), ethnohistorical, and historical as methodological approaches in my research in search of Debwewin (truth). Therefore, both the content and methodology of this thesis adds to the body of knowledge to the field of Indigenous Studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".