It's in the Blood: Theory and Praxis of Lifelong Indigenous Education
Bibliographic record
Abstract
Through the voice of a Metis educator, this work addresses the foundations of an Indigenous lifelong education. Lived experiences connect with unfolding personal narrative to demonstrate the ancient flow of Indigenous knowledge, and the continuity and expression of Indigenous being. The narratives implicitly references connections and relationships between people and land as vitally necessary for Indigenous learning and the survival of Indigenous peoples as distinct and whole human individuals and collectives. The concept of ‘blood memory’ is presented as foundational to the narrative and repositions a content that might otherwise align closely with readily accessible and acknowledged renewal within Indigenous education. This work does not speak from within the theoretical canons of education and schooling as these are upheld, adhered to, and promoted by Western intellectual traditions of knowledge. It offers analytical, critical thinking derived from the lived experiences and acquired learning of an Indigenous educator. The narratives demonstrate that lifelong learning is gifted and accepted through intentional individual and collective participation within a flow of knowledge transmission and transformation grounded upon generations of ancestral research in the development, validation, sharing, practice, and renewal of praxes that support everyday living and dying.
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 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 | 0.006 | 0.034 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".