MétaCan
Menu
Back to cohort
Record W7145051452

北海道医療大学生の海外英語研修に関する意識調査の分析

2024· article· ja· W7145051452 on OpenAlexaboutno aff
亜矢子 白鳥, ホガード ショーン, 俊彦 足利, 博史 塚越

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2024
Typearticle
Languageja
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacy and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsStudy abroadVariety (cybernetics)
DOInot available

Abstract

fetched live from OpenAlex

The number of Japanese studying abroad has been declining. Similarly, at Health Sciences University of Hokkaido, the number of students participating in language programs at the University of Alberta, Canada, has gradually declined since its peak in 1998. However, no study has analyzed the reasons for the decline in the number of students studying abroad. Therefore, the purpose of this study is to explore students' interests and concerns regarding study abroad. The researchers surveyed 656 first-year students about studying abroad. The results showed that nearly 70% of the students were not interested in studying abroad, and many of those who were interested preferred less expensive and shorter programs. As for desired destinations, the United Kingdom and Australia were ranked first, but students were interested in a variety of regions, including the Philippines and Singapore. Thus, there is a need to improve study abroad programs, taking into account the students' perspectives.

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.005

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 head0.129
GPT teacher head0.465
Teacher spread0.336 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Repositories DataBase (IRDB)Same topicPharmacy and Medical PracticesFrench-language works237,207