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Record W4234218592 · doi:10.5871/jba/009s7.107

Developing climate-responsive cities: exploring the environmental role of interstitial spaces of Santiago de Chile

2021· article· en· W4234218592 on OpenAlexfundno aff
Cristian Silva

Bibliographic record

VenueJournal of the British Academy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American Urban Studies
Canadian institutionsnot available
FundersComisión Nacional de Investigación Científica y TecnológicaQueen's UniversityQueen's University Belfast
KeywordsUrban sprawlGeographyMetropolitan areaSustainabilityEnvironmental planningEconomic geographyAdaptation (eye)Land useEnvironmental resource managementCivil engineeringEcologyEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Drawing upon a range of writing on suburbanisation and urban sprawl, this paper outlines an approach to the analysis of interstitial spaces of urban sprawl. Such spaces are the outlying geography of metropolitan regions existing in-between developed or urbanised areas. As such, they constitute an eclectic mix of open spaces, natural areas, obsolete infrastructures, geographical restrictions, farming land, etc, that alternatively contribute to the city�s environmental and functional performance. Despite being identified in the literature, there has been little recognition of interstitial spaces as part of the environmental sustainability of urban systems, and how they support cities in improving their resilience and adaptation capacities. Using the case of Santiago de Chile, this paper highlights an environmental approach to studying the interstices and the need to examine such spaces at different scales linked to their respective environmental potentials.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the British AcademySame topicLatin American Urban StudiesFrench-language works237,207