Casting a New Light on a Long Shadow: Saskatchewan Aboriginal High School Students Talk About What Helps and Hinders their Learning
Bibliographic record
Abstract
What do teachers do (or not do) that makes you want to go to school? A team of Saskatchewan researchers asked Saskatchewan Aboriginal high school students this question about the aspects of instructional practice that helps and hinders their learning. While responses pointed to several aspects, teacher relational instincts and capacities were the most influential in school engagement for this group of Aboriginal students. Students in this study described three relational capacities of effective teachers: a) empathetic responsiveness to the student as whole being, b) the degree to which teacher disposition influenced the relational dynamic with students, and c) teachers’ responsiveness to the full context of the student’s life (including a sensibility of the student’s Indigenous culture). Through a case study process, focus group interviews were conducted in six Saskatchewan schools. The study included 75 Aboriginal high school students from six schools (urban, rural, provincial, and First Nations band schools) in Saskatchewan, Canada. The qualitative case study research design was informed by Indigenous principles, and the theoretical lens employed in the analysis relied predominately upon an Indigenous theoretical perspective, as articulated by Smith and Perkins (as cited in Kovach, 2014). The findings point to the teaching attributes of relationality, responsibility, and understanding of contextuality identified within an Indigenous theoretical framework as influential in fostering engaged learning environments for this group of Aboriginal high school students.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| 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".