MétaCan
Menu
Back to cohort
Record W4389161650 · doi:10.55016/ojs/ajer.v64i3.56514

Postgraduate International Students’ Living and Learning Experience at a Public University in British Columbia

2018· article· en· W4389161650 on OpenAlexvenueaboutno aff
Luis Miguel Dos Santos

Bibliographic record

VenueAlberta Journal of Educational Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
FundersWoosong University
KeywordsPedagogyPsychologyPublic universityMathematics educationSociologyMedical educationPolitical scienceMedicinePublic administration

Abstract

fetched live from OpenAlex

Canada is a rich and diverse country that attracts many international students and immigrants to expand their horizon.According to Statistics Canada (2017), nearly 30% of British Columbia total population speak a mother tongue that is a language other than English.The statistics indicate that besides Caucasian Canadians, other ethnical groups can live in Canada without barriers.Canadian higher education institutions attract many international students for educational and research purposes and provide a welcoming community, due to their well-known educational qualities.Currently, there are 11 public higher education institutions and five private higher education institutions in British Columbia.According to Global Affairs Canada (2016), the international student population has increased significantly.From last decade, the total population of international students has increased from 114,093 in 2000 to 218,245 in 2010.The increasing percentage was nearly 100%.The report also indicated that the student population classified as university students had an 8% of annual growth rate.Based on the above statistics, Canadian higher education institutions are considered as one of the most popular destinations for international students to seek degrees.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.083
GPT teacher head0.420
Teacher spread0.337 · 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

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueAlberta Journal of Educational ResearchSame topicInternational Student and Expatriate ChallengesFrench-language works237,207