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Record W2529609906 · doi:10.2495/sdp-v11-n6-930-938

Planning and urban growth. What to do with urbanized vacant areas in the land of Valencia?

2016· article· en· W2529609906 on OpenAlexvenueno aff
F. Gaja i Díaz

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsValenciaUrban planningEnvironmental planningLand-use planningLand useUrban sprawlGeographyRegional planningEnvironmental scienceCivil engineeringEngineering

Abstract

fetched live from OpenAlex

In 1996, an expanding real estate property cycle of unusual magnitudes began in the Kingdom of Spain, to abruptly cease in 2007. Its economic, social and political logic has been to this day widely studied, but instead the contribution of urban planning as a driver and impeller of proposals of unviable urban overgrowth has received scant attention. In this paper, we shall consider the role played by urban planning with disparate proposals in the so-called construction bubble. By studying relevant case studies, we will evidence the impact that of over planning has had on the environment and natural resources. In 1994, it was approved for the Community of Valencia, a ground-breaking law, that allowed real estate agents to develop areas in which they had not any property even against the opinion and the will of the landowners. The facilities given to developers, in a context of abuse and corruption, have taken their toll after the bursting of the housing bubble. Our goal is to analyse the effects and consequences of these actions: the destruction of the landscape, the consumption of natural resources beyond their capacity for regeneration, the development of areas that today remain vacant, with special emphasis on the latter.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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