"It was your ancestors that put them there and they put them there for you" : exploring Indigenous connection to mazinaabikiniganan as land-based education
Bibliographic record
Abstract
This study explored Indigenous connections to mazinaabikiniganan (more commonly known as \nrock art or pictographs) and investigated how these sites contribute to land-based education. \nFocused on the community of Batchewana First Nation and their relationship to the \nmazinaabikinigan of Agawa Rock located within Lake Superior Provincial Park, this study used \nsnowball sampling to identify six knowledgeable community members who shared their stories, \nknowledge, and understanding of the mazinaabikiniganan as well as other sites of significance \nwithin their traditional territory. Using storywork and conversation as method, data was gathered \nthrough conversations held with community members rather than formal interviews. The stories \ncollected indicate that mazinaabikiniganan must be understood from within a larger frame of \nreference, emphasizing the importance of geographical, political, and historical context. \nAdditionally, stories showed the ceremonial and spiritual significance of place, affirmed \nAboriginal rights and sovereignty within traditional territory, and highlighted the importance of \nlife-long learning and decolonizing education. The thesis weaves together the findings and \ndiscussion to provide a cohesive picture of how the community values and perceives this site and \nconcludes with recommendations on the pedagogic potential of mazinaabikiniganan on a broader \nscale.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| 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".