Measuring Quality of Human Community Life by Spatial-Temporal Age Group Distributions—Case Study of Recovery Process in a Disaster-Affected Region
Bibliographic record
Abstract
This study proposes an effective method of measuring the quality of a community, calculated from spatial-temporal age group distributions. For this purpose, niche indices, which are used in ecology, are employed as measurement techniques and are interpreted in terms of safety and communication. Traditional indices are examined theoretically by using spatial statistics and are shown to be essentially identical. This paper also proposes a special niche index for disaster risk evaluation. From the fact-finding studies in Kobe City, Japan, which was severely damaged by the 1995 Great Hanshin-Awaji earthquake, it is inferred that the niche index may possibly pertain to damage reduction. Further, community health in the recovery process in the Nagata Ward, Kobe City is evaluated by using the niche indices and related statistical tests. The results show that the quality of the community deteriorated after the disaster even in the area where the building recovery speed was relatively rapid.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".