School Engagement Among Aboriginal Students in Northern Canada: Perspectives From Activity Settings Theory
Bibliographic record
Abstract
BACKGROUND: Educational disengagement is a public health concern among Aboriginal populations in many countries. It has been investigated previously in a variety of ways, with the conventional focus being on the children themselves. Activity settings are events and places, theorized in terms of their symbols, roles, time frame, funds, people, and physical location. According to the theory, particular behaviors and experiences are shaped by different configurations among these elements. This study explored how activity settings theory might provide new insight on school engagement. METHODS: Ethnographic study was undertaken at a grades primary to 12 school in a remote First Nations community in Canada's Northwest Territories. We collected data through interviews, focus groups, archival material, and field notes from 7 months of participant observation. An activity settings model acted as template for data collection and interpretation. RESULTS: Different aspects of the school's physical layout, routines, procedures, transport systems, mix of people, and rules were able to be systemically assessed and classified as either creating or eroding engagement. CONCLUSION: This study applies an activity setting analysis to school engagement, thereby allowing researchers to investigate the dynamic and nested nature of context or environmental influences on engagement. It provides grounded observations that invite direct opportunities for action on dimensions that teachers and practitioners might not otherwise "see."
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 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".