MétaCan
Menu
Back to cohort
Record W4224305708 · doi:10.5539/hes.v12n2p126

On Motivations for Southeast Asian Doctoral Students’ Studying at Japanese Private Universities

2022· article· en· W4224305708 on OpenAlexvenueno aff
Tsuneji Futagami

Bibliographic record

VenueHigher Education Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsAnimeJapanese languageHigher educationStudy abroadJapanese culturePolitical scienceTrend analysisSociologyPsychologyLibrary sciencePedagogyJapanese studies

Abstract

fetched live from OpenAlex

It was investigated why Southeast Asian recipients of engineering or related fields studied at Japanese private universities. Scholarships were the most popular reason. The reasons that they liked Japan and that the research or education level at Japanese universities was high were less popular. About a half of questionnaire respondents had been to Japan before they studied at Japanese language institutes or at Japanese universities. More than ninety percent of respondents were interested in Japanese culture before they studied at Japanese language institutes or at Japanese universities. These implied that they had advance knowledge on Japan before they studied in Japan. Correlation analysis implied that Japanese anime or cartoons would be one of indirect causes of Southeast Asian doctoral students’ studying at Japanese private universities. Analysis of international students’ voices on Japanese private universities’ official web pages showed that one reason why they were motivated to study at Japanese private universities was interest in the Japanese language and Japanese culture. This is consistent with the questionnaire survey.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.092
GPT teacher head0.393
Teacher spread0.301 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHigher Education StudiesSame topicHong Kong and Taiwan PoliticsFrench-language works237,207