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Record W7001265435

Issue 08: New Policies, New Students, New Direction? Trends in International Student Enrollment in Ontarioâs Changing Policy Landscape

2016· article· en· W7001265435 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2016
Typearticle
Languageen
FieldMathematics
TopicStatistics Education and Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusResidenceWork (physics)Higher educationQuality (philosophy)International education
DOInot available

Abstract

fetched live from OpenAlex

International students bring immense benefits to Ontario’s postsecondary system and labour market through the financial boon they bring to universities and colleges, their cultural diversity, the positive economic impacts they can have on Canadian society after graduation, and the skills they develop and contribute. However, many international students may find it difficult to transition to permanent residence after graduation, or find the career they seek immediately upon completion of their studies. In addition, little is known about the number of international students transitioning to the labour market, their socioeconomic outcomes, or their success in doing so. The present analysis sought to identify the number of international students who entered Ontario from 2000 to 2012, their demographic and socioeconomic characteristics, identify trends in their entry, and identify the ways they most commonly transition to the labour market. It also identified the main policies guiding international student recruitment and transition, and noted the policy changes that would have the most direct effect on international students. This brief summarizes the findings from a research project for the Higher Education Quality Council of Ontario in 2013-2014.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.374
Teacher spread0.312 · 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.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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