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Record W1964443423 · doi:10.1068/b31103

Improving Governance Arrangements in Support of Sustainable Cities

2005· article· en· W1964443423 on OpenAlex
Ellen van Bueren, Ernst ten Heuvelhof

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.

Bibliographic record

VenueEnvironment and Planning B Planning and Design · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsCorporate governanceIncentiveContext (archaeology)BusinessSustainable developmentQuality (philosophy)Economic systemPolitical scienceEconomicsMarket economyFinance

Abstract

fetched live from OpenAlex

Governance to support sustainable development always seems to encounter the same difficulties. The chances of successful governance increase when governance arrangements are better tuned to the environment that it tries to change. However, a better fit leaves less room for change. Governance arrangements supporting sustainable development are more prone to failure, as they aim at changing that environment. Radical institutional change is at the core of sustainable development, but without the help of external factors, such as major crises like the oil crisis in the 1970s, the sense of urgency for such radical change is lacking, and incremental change seems to be the only road available. The authors explore how governance arrangements deal with this recurring barrier to institutional change. Their conclusion is that the more governance arrangements respect the institutional context in which they are used, the higher their quality. To speed up the incremental track, the design of governance arrangements should include positive incentives for actors to cooperate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.304

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 communication0.0000.000
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 head0.048
GPT teacher head0.318
Teacher spread0.270 · 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