Early Learning Experiences of Post-Secondary Bangladeshi Students with a Study Permit Participating in an Online Indigenous Learning Event
Bibliographic record
Abstract
This project explores the early learning experiences of Bangladeshi students on a study permit in Alberta, Canada after their participation in an online, asynchronous Indigenous-created learning event comprised of a video that explores issues of colonially imposed ideas around Indigenous identity and other colonial injustices. In this community-based mixed-method study that drew on principles of action research, I explored participants’ early learning experiences vis-a-vis Indigenous peoples in Canada in an informal setting and the challenges encountered in learning more about Indigenous peoples in universities across Alberta, Canada. The action research framework that informed my study guided me to take a solution-focused approach where, based on my findings, I suggest the need for mandatory learning in post-secondary intuitions for international students about Canada’s colonial past, before entering on the work of reconciliation. Due to the complexity of reconciliation, entering reconciliatory work requires careful and considered preparation in tandem with Indigenous peoples. The findings provide a broader view of how early learning experience ignited curiosity and awareness about Indigenous topics among participants, how they made meaning of reconciliation and post-secondary intuitional responsibility to create a mandatory learning session that is accessible, cost-free, and unevaluated by collaborating with Indigenous peoples.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".