Japanese metropolitan structure defined through correlated demographics and local service sector employment provision
Bibliographic record
Abstract
The relatively recent shift from an industrial to a post-industrial society has produced significant changes in the structure of metropolitan areas at a global level. Following the communication revolution and implicitly a spatial dispersion of economic centres, the metropolis becomes a polycentric mass with increased flexibility and less clear boundaries. While the process of global urbanisation continues, most urban growth happens in the urban periphery, which gains a key role in regional development, often even competing with central cities. Highly developed metropolitan areas beyond the core city are now essential for urban competitiveness. Polycentric development and the post-industrialisation of metropolitan peripheries happens in Japan in the particular context of population ageing and decline which, through decreasing densities, impacts the service provision, infrastructure and the urban fabric as a whole. Through statistical analysis, this paper investigates the correlation between local tertiary service employment provision and population evolution between 1995 and 2015, in the three largest major metropolitan areas in Japan, Tokyo, Keihanshin and Chukyo. Furthermore, a combined quantitative and qualitative approach was used in order to identify, within the three metropolitan areas, regions where service sector employment is high and correlated with population growth. The study is intended to serve as a possible basis for further metropolitan restructuring that can tackle population and implicitly urban shrinkage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".