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Factors Affecting Late Twentieth Century Land Use Patterns in Kamakura City, Japan

2009· article· en· W1989472117 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeographical Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of Tokyo
KeywordsUrban sprawlZoningGeographyUrbanizationLand usePopulationUrban planningPopulation growthEnvironmental protectionEconomic growthPolitical scienceCivil engineeringDemography

Abstract

fetched live from OpenAlex

Abstract Land use patterns can be viewed as a reflection of various factors including zoning regulations and environmental and social influences. To understand the effects of these factors, late twentieth century land use data for Kamakura City, Japan were analysed in relation to zoning regulations and geomorphological influences using geographic information systems techniques. Kamakura is a typical example of an Asian historic city experiencing the pressures of recent urbanisation. Statistical analyses, including principal component analysis, were employed to identify factors affecting changes in major land use patterns over time and space. The rapid increase in population and government regulation in the 1970s led to the construction of low‐rise buildings in piedmont areas. However, topography and conservation activities limited construction to areas with slope angles below about 10°. In the late 1980s and early 1990s, the area of vacant land on the urban lowlands increased due to the large increases in land value during the Japanese Bubble Economy phase. Land use intensified in most urban areas, although hilly areas were still characterised by low‐rise buildings. Although urban sprawl has occurred in many cities in Asia, this has been limited in Kamakura because of strong land use regulation and conservation activities. However, the city has experienced high‐rise development in its urban lowlands.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.059
GPT teacher head0.318
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it