MétaCan
Menu
Back to cohort
Record W4236791117 · doi:10.32920/ryerson.14646477

Service needs and gaps for international students transitioning to permanent residency in a "two-step" immigration process : a Toronto-based study

2021· preprint· en· W4236791117 on OpenAlexaffabout
Erin Roach

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsImmigrationGovernment (linguistics)Service (business)Settlement (finance)Political sciencePopulationPublic relationsEconomic growthPublic administrationSociologyBusinessMarketingEconomicsLawFinance

Abstract

fetched live from OpenAlex

Despite the increase in efforts to attract and retain international students in Canada, including the introduction of the Canadian Experience Class in 2008, there has been little investigation into what supports will assist international students as they transition from students to workers to migrants. This research paper is a Toronto-based investigation of the service needs and gaps that exist for international students aiming to transition to permanent residency in Canada. Data gathered from interviews with front-line workers assisting international students, an immigrant-serving organization, and government suggests that immigration policy reforms aiming to attract and retain international students have not been accompanied by the necessary changes to traditional settlement and international student services resulting in service gaps for this segment of Canada's international student population. The present study also connects these findings to neoliberal immigration policies and practices in place in Canada since the 1990s.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.082
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.002
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.402
Teacher spread0.370 · 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 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

Citations19
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicInternational Student and Expatriate ChallengesFrench-language works237,207