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Record W2042538166 · doi:10.1177/0739456x0202100402

Deliberative Planning and Decision Making

2002· article· en· W2042538166 on OpenAlexaff
Tore Sager

Bibliographic record

VenueJournal of Planning Education and Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsTransport Canada
Fundersnot available
KeywordsAnalogyLegitimacyDemocracyRationalityDeliberative democracyDeliberationArrowPlan (archaeology)ImpossibilityPoliticsSocial choice theoryManagement scienceLaw and economicsSociologyComputer sciencePolitical scienceEpistemologyEconomicsLawMicroeconomics

Abstract

fetched live from OpenAlex

Much communicative planning is consensus oriented and rests on ideas of deliberative democracy. Planning recommendations made by dialogue are based on the intellectual force of arguments giving reasoned rankings of the planning alternatives. Dialogue encompasses the amalgamation of arguments in accordance with democratic criteria ensuring the communicative rationality of the process and the legitimacy of the recommendation. The balancing and weighing of arguments should avoid decision cycles that would make the recommendation of a plan arbitrary. By an analogy with Arrow’s theorem on the general impossibility of consistent and fair social choice, it is demonstrated that dialogue cannot ensure consistent recommendations and simultaneously prepare for political decision making in a democratic manner. The result is valid for debates over planning alternatives when differences in quality are not comparable across all the important arguments (concerning noise, safety, visual standard, social impact, etc.), which is the most common situation.

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)0.023
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0040.042
Scholarly communication0.0140.012
Open science0.0030.009
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0140.003

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 head0.156
GPT teacher head0.449
Teacher spread0.293 · 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

Citations41
Published2002
Admission routes1
Has abstractyes

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