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Record W6903251655 · doi:10.11575/prism/39793

Crossing the Divide: Reconciling International Student Migration and Indigenous Peoples

2022· other· en· W6903251655 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousImmigrationNexus (standard)Extant taxonTraditional knowledgeInternational relations

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0570.001

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.

Opus teacher head0.045
GPT teacher head0.353
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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