Okiskinwahamâkew: Reflecting on teaching, learning and assessment
Bibliographic record
Abstract
This paper looks at assessment views held by Alberta Education in regards to teaching and learning for educators in Alberta. The standardization model of teaching and assessment excludes Indigenous thought systems articulated through rigorous thought processes in the nehiyaw mâmitoneyihcikan – the Cree mind and intelligences. Infusion, integration, indigenization models that privilege the dominant educational design continue to perpetuate an invisible colliding space that impacts the Indigenous thinker and learner. Privileging Indigenous language thought systems that are rich in multidimensional processes are presented to address current notions of teaching and assessment. Looking through the lens of the Indigenous language system and addressing the politics of literacy uncovers nehiyaw mâmitoneyihcikan – the Cree mind. This rich thought system reveals a sophisticated system that operates omni and multidimensionally from and within a compassionate mind – a value based way of seeing and engaging. Honoring nehiyaw thought systems, processes of coming to know and respecting Indigenous understandings of teaching and learning, lead to considering the rigorous nehiyaw understanding of okiskinwahamâkew – Indigenous informed teaching guide.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".