Bibliographic record
Abstract
In Japan, based on the Act for the Eliminating Discrimination against Persons with Disabilities in 2006, all business operators have been obliged to provide reasonable accommodation from April 2024 onwards. Universities have been working to develop support systems including the physical environment, but it is difficult to share information about reasonable accommodation due to the need to protect personal information, and there is not much research on the subject. In particular many aspects of activities in the classroom are left to the judgement of the lecturers, and in Japanese language classes, which often include collaborative activities, there are many lecturers who struggle to respond to students who have difficulty participating in these activities. In this paper, based on interviews to relevant staff conducted at universities in Canada, Australia and South Korea, we will clarify that the number of students with learning disabilities and other characteristics that are not easily apparent from appearances is increasing worldwide, and that this is leading to a fundamental shift in teaching and learning. We will then consider the environment and particularly the role of lecturers necessary for creating inclusive classroom settings, using Japanese language lessons at Hokkaido University as a reference in future classroom activities.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".