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Record W4390191464 · doi:10.5206/cie-eci.v52i2.16326

Study Abroad at an Ontario College: Towards More Accessible and Inclusive Programming

2023· article· en· W4390191464 on OpenAlexaffvenueabout
Amira El Masri, Noah Khan

Bibliographic record

VenueComparative and International Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsStudy abroadPolitical sciencePublic relationsMedical educationPsychologyEconomic growthPedagogyMedicineEconomics

Abstract

fetched live from OpenAlex

Despite Canada’s success in attracting international students to its postsecondary campuses, it sends very few domestic students abroad, and especially so from its college sector. This paper offers a brief overview of Canada’s policy approach to study abroad, literature review on students’ participation in study abroad, and outcomes of a study on students’ (perceived) barriers at a college in Ontario, Canada. Students at the college were surveyed to examine their attitudes towards study abroad participation and their perceived barriers regarding study abroad. The study found that students were overwhelmingly interested in study abroad but perceived strong barriers to participation, findings which are consistent with the literature: financial, academic, social/familial barriers, and accessibility, safety, and support concerns. These findings suggest that through expansion of national programming, coordination of provincial strategy, and inclusive, accessible policies and programming at the institutional level, more college students will be able to receive the many documented benefits of study abroad experiences.

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)0.000
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.146
GPT teacher head0.503
Teacher spread0.357 · 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
Published2023
Admission routes3
Has abstractyes

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