Making the classroom a healthy place : the development of affective competency in Aboriginal pedagogy
Bibliographic record
Abstract
This thesis explores the development of affective competency in Aboriginal pedagogy through the exploration of the Native Training Institute (NTI), an institute that functioned from 1980 to 1987 in Kamloops, British Columbia. Ten students, two administrators arid one elder were interviewed to explore how the processes of affective education were included in the NTI curriculum. The thesis develops a theory of educational transformation based on the educational principles developed at the Native Training Institute that posits a theory of affective development founded on Aboriginal knowledge, learning identity, values, competencies, ideals and vision. Four arguments for the inclusion of affective education in contemporary curriculum are presented. First, the Indigenous assertion that emotions and values are essential to the decolonization process and therefore necessary for Aboriginal success in the educational environment is defined. Second, the argument of modern European philosophy that affect is more essential to the process of learning than has been previously thought. Third, the recent developments in cognitive science that uphold the Aboriginal world view that thinking and feeling are not only connected but that emotion plays the major role in the functioning of mind and memory. Fourth, the comments of the students from the NTI that the affective aspect of the curriculum at the institute was essential to their learning.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".