Culturally responsive policy development: Co-constructing assessment and reporting practices with First Nation educators in Alberta
Bibliographic record
Abstract
Abstract Informed by an adaption of the tri-level reform framework, we collaborated with a First Nation district student assessment committee, school principals, and district personnel to develop a student assessment policy. Through a series of workshops and meetings with school administrators and classroom teachers from Tsuut’ina Nation, located in southern Alberta, Canada, we created an assessment, evaluation, and reporting policy aligned to Tsuut’ina fundamental values, provincial priorities, and best practices in student assessment. Teaching practices that are aligned to the three educational pillars of learner outcomes, instruction, and assessment, as well as the Tsuut’ina fundamental values, have the potential to impact the Nation’s student educational success. We discuss implications of this work in relation to collaboration, Indigenous world view, and outcome-based reporting.
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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 | 0.149 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.022 | 0.008 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".