Crossing the Divide: Reconciling International Student Migration and Indigenous Peoples
Bibliographic record
Abstract
Reconciliation rests at the nexus of relationships between immigrants and Indigenous peoples of Canada. Setting out this literature review was focused on providing an environmental landscape on what has been researched on the reconciliation between international students, Canadian higher education, and Indigenous peoples. However, as this comprehensive literature review will demonstrate there is considerable extant literature regarding related topics, new immigrant transitioning, socio-cultural and historical contexts, contestations, and decolonizing initiatives within universities and communities, which while related and offer opportunities of engagement, do not delph deep into Canadian higher education’s role (as an economic immigration pathway) in the reconciliation of international students (as potential new immigrants and settlers) and Indigenous Peoples’ Whilst this literature review explores key concepts and contestations its’ overall purpose has been to reveal gaps, and crevices, which demonstrate the need for research into Canadian higher education’s ethical and fraught role into reconciling international students and their relations with Indigenous peoples. This literature review is followed by research recommendations focused on addressing the gaps identified and formed around two key questions: 1. how do international students’ perceptions about Indigenous peoples change and 2. how might this contribute to reconciliation, if at all?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.021 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".