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Record W4378650681 · doi:10.7202/1099986ar

Hosting Early Study Abroad Students in Ontario: Internationalization of Education Dynamics in Secondary Schooling

2023· article· en· W4378650681 on OpenAlexaffvenueabout
Nancy Bell, Paul Tarc, Sandra R. Schecter, Alyssa Racco, Haoming Tang

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsWestern UniversityYork University
Fundersnot available
KeywordsInternationalizationVisionThematic analysisStudy abroadPolitical sciencePedagogyDynamics (music)Comparative caseInternational educationHigher educationPublic relationsQualitative researchSociologyBusinessSocial science

Abstract

fetched live from OpenAlex

This study illuminates the current policy and practice dynamics and tensions of school internationalization in the province of Ontario generated by the increasing presence of international students at the secondary school level, identified as early study abroad (ESA) students. It conducts a comparative thematic analysis of a set of interviews with school- and board-level stakeholders of internationalization alongside a critical policy analysis of a key provincial policy text. We find that ESA-based internationalization is largely run out of internationalization offices resourced to focus on student recruitment and administrative support, with oversight of homestay and custodianship being significant components. The more idealistic visions of school internationalization emphasized in provincial policy and some school discourse occur in a more reactive fashion. On-the-ground educational support of these newcomer ESA students is shouldered by schools and educators within their existing and limited capacities, while the intercultural dimensions and benefits remain largely aspirational.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.023
GPT teacher head0.396
Teacher spread0.372 · 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 designObservational
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

Citations4
Published2023
Admission routes3
Has abstractyes

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