A Comparative Inquiry of Teaching Strategies in New Zealand and Canadian High Schools: A Global Quest for Improved Educational Outcomes for Indigenous Students
Bibliographic record
Abstract
Abstract Indigenous students that live in poverty experience contextual socio-economic factors with residual effects of lower educational outcomes than their non-Indigenous counterparts. Indigenous children that live in poverty often have fewer resources, are segregated, and continue to be marginalized in the classroom. The vicious cycle of low education levels for Indigenous peoples confines them to low paying employment or unemployment that results in ongoing poverty or being a statistic categorized as the working poor. The purpose of this research was to gain a better understanding of the strategies that teachers have animated in their classrooms, which they perceived to be successful in encouraging Indigenous students to attend school, remain in school, complete course credits, and persevere to graduate from high school. The intent was to discover the how-to strategies and advance working knowledge of pedagogical practices leading to improved educational experiences and achievement levels for Indigenous students. This chapter will present the observations and qualitative findings of the case studies conducted in New Zealand and Canada, wherein 14 teachers described what they did and what it looked like in their classrooms. A constructivist approach was utilized to make meaning and gain the interpretations from the participants. This was achieved by first viewing the interactions in the classrooms and, through the interview process, being able to garner a better understanding of what was witnessed from the point of view of the participants.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".