Japanese University Students’ Attitudes towards Globalisation, Intercultural Contexts and English
Bibliographic record
Abstract
This is a study conducted at Nagoya University, a top Japanese national institution, on undergraduates’ attitudestowards globalisation, intercultural contexts and English. Globalisation takes place in a varied context in Japan whichincludes the sakoku (closed country) mentality as well as government rhetoric encouraging all to embraceglobalisation. According to the literature on internationalisation of higher education, intercultural contexts resultfrom globalisation and educators must prepare students to function in these contexts. Students, however, may or maynot see the future in the same way educators and policy-makers do. Attitudes towards English are mixed: some see itas an indispensable communicative tool for the future while others think of it as a test score which helps them securejobs or places in graduate programmes. The author discovered in this study that while most of the students’ attitudesecho government rhetoric, they think globalisation is something they can opt out of. In addition, even though theyfeel that the ability to function in intercultural contexts is desirable, half of them do not think they will findthemselves in these contexts, which may compromise the effectiveness of curriculum which have been planned basedon the assumption that students are going to be in intercultural contexts in future. They are also protective ofJapanese culture and very concerned about their English communicative skills.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".