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Record W4324130820 · doi:10.32674/jis.v14i1.5347

ISM Policy Pervasion

2023· article· en· W4324130820 on OpenAlexaboutno aff
Max Crumley-Effinger

Bibliographic record

VenueJournal of International Students · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Variety (cybernetics)Political sciencePublic relationsAffect (linguistics)SociologyFocus groupPsychologySocial science

Abstract

fetched live from OpenAlex

With more and more literature on international student mobility and migration (ISM), one area of focus has often been overlooked: the impacts of student visas and study permits. Examined through an institutionalist framework highlighting the influences of institutions on individuals and their agency, this study describes how visa and study permit policies pervades international students’ lives in a variety of ways. Interview data collected from 40 international students who study in Australia, Canada, and the United States were analyzed to uncover themes from these host countries. Drawing on these interviews to outline the concept of ISM policy pervasion, the findings of this study show that visa policies affect international students in wide ranging ways. In addition to providing empirical evidence for ISM policy pervasion, this article also lays the groundwork for further studies that delve into the practical impacts of student visa and study permit policies around the world.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.027
GPT teacher head0.434
Teacher spread0.407 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2023
Admission routes1
Has abstractyes

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