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Record W3040074229 · doi:10.1016/j.cities.2020.102816

Under pressure: Factors shaping urban greenspace provision in a mid-sized city

2020· article· en· W3040074229 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCities · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityAustralian Government
KeywordsCorporate governanceContext (archaeology)Government (linguistics)TechnocracyLocal governmentPopulationBusinessEnvironmental planningEnvironmental resource managementGeographyPoliticsPolitical sciencePublic administrationEconomicsSociologyFinance

Abstract

fetched live from OpenAlex

Urban greenspaces provide diverse ecosystem functions, services and benefits to residents. Much commentary has been offered to date about citizens' demands for more urban greenspace. Less attention, however, has been given to the 'supply side' pressures experienced by local government in delivering urban greenspace, particularly in mid-sized cities. Greater attention to factors shaping supply is warranted, especially in the context of rapid population growth. By understanding how existing greenspace provision approaches can stymie the efforts of local government to meet citizens' needs, new approaches can be identified. This paper assesses several factors shaping urban greenspace provision in Surrey - a city within the Greater Vancouver area. Insights are derived from in-depth interviews with key stakeholders, public documents, and census and municipal data about parks and their context as a specific type of greenspace. Our findings suggest that governance tools, economy and property markets, and financial and natural resources manifest as core factors influencing urban greenspace provision in Surrey. A reliance on governance tools premised upon standards has created park provision paradoxes. Treating greenspace provision as a largely technocratic exercise may be limiting Surrey's ability to respond to changing politics, economics and population trends. We point to alternative approaches.

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)0.000
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 score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.262
Teacher spread0.197 · 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