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Record W2134157009 · doi:10.1068/a43164

Investigating the Knowledge interface between Stakeholder Engagement and Plan-Making

2010· article· en· W2134157009 on OpenAlexaboutno aff
Crystal Legacy

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
FundersJohns Hopkins University
KeywordsDeliberationStakeholderPlan (archaeology)Stakeholder engagementProcess (computing)LegitimacyProcess managementContext (archaeology)Political scienceBusinessPublic relationsComputer sciencePoliticsGeography

Abstract

fetched live from OpenAlex

The ‘ideal deliberative procedure’ provides structure to the process of stakeholder deliberation, yet creates a tension with the formal processes of strategic plan-making. This paper examines process design by drawing upon communicative planning theory, and the rational comprehensive model and deliberative democracy literature. In the context of metropolitan strategic spatial plan-making, the aim of this paper is to examine how the knowledge interface between the process of stakeholder engagement and the process of plan-making enables or inhibits implementation of the plan. A retrospective study examining the development of two metropolitan strategic spatial plans: Greater Perth's the Network City plan and Greater Vancouver's the Livable Region Strategic Plan is provided. It is revealed that the engagement of the planners, the public and the politicians occurs within formal stakeholder engagement ‘events’ positioned at different stages of the plan-making process. This paper reveals that the deliberation among the professional planners and the politicians at the process design stage steers the plan-making process in a manner that retains its legitimacy and creates a more implementable plan.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.668

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 studies0.0010.000
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 head0.071
GPT teacher head0.277
Teacher spread0.206 · 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

Citations46
Published2010
Admission routes1
Has abstractyes

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