Questionnaire Survey on the Difficulty of Attending Work for Commuters After the 2018 Osaka Earthquake
Bibliographic record
Abstract
This paper presents the results of a questionnaire survey conducted on those who had difficulty commuting after the 2018 Osaka earthquake. As with the Great Hanshin-Awaji Earthquake, serious traffic congestion occurred in downtown Osaka following the 2018 disaster. Based on the questionnaire survey on those who had difficulty commuting, which is considered to be a factor of traffic congestion, it was found that 60–70% commuted as usual after the earthquake; about half of the commuters who usually take the train changed their method of commuting, one-quarter of whom used automobiles; there were very few who experienced problems in their work because they had not gone to work or their workplace had closed down for the day; and many felt that it would be better to receive instructions on work attendance in the aftermath of an earthquake. The present study points out the need for companies and society to adopt rules so that those who find it difficult to commute will refrain from going to work and remain in their local communities to help others, except for those in certain occupations or positions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".