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Record W4402585856 · doi:10.33524/cjar.v24i2.665

Identities in Transition from Africa to Canada: Becoming Students

2024· article· en· W4402585856 on OpenAlexaffvenueabout
Abigail Amoakoa Okyere, Marian Orhierhor, Andrews Nartey, Judith Nuhu, Anne Ayomiposi Joseph, Atang Koboti, Philip Kimani Karangu, Cynthia Nicol

Bibliographic record

VenueThe Canadian Journal of Action Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransition (genetics)Action researchMathematics educationPedagogyPolitical scienceSociologyGender studiesPsychologyBiology

Abstract

fetched live from OpenAlex

Students studying abroad are faced with challenges that impact their cultural, social, and economic identities, and this varies greatly depending on their home country and study destination. The transition and inter-cultural learning experiences of international tertiary students from African countries are currently under-examined. Afrocentric theory was employed to interpret the data derived from this qualitative study, which drew upon participatory action research and Photovoice methods to explore how African students navigate transitions to studying in Canada and the strategies they use for creating supportive social resources. As authors, co-researchers, and participants, we identified unique insights on how students build and maintain senses of connections, familiarity, and comfort when away from home, and how they conceptualize, create, and sustain community. These accounts provide insight for mentors, faculty, and policymakers in North American institutions on how they can offer opportunities for holistic learning, cultural integration, and access to valuable mentorship to help students navigate the complex journey of transition.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.130
GPT teacher head0.409
Teacher spread0.279 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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
Published2024
Admission routes3
Has abstractyes

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