MétaCan
Menu
Back to cohort
Record W2803322151 · doi:10.1177/1473095218776042

The moral limits of autonomous democracy for planning theory: A critique of Purcell

2018· article· en· W2803322151 on OpenAlexaff
Victor Bruzzone

Bibliographic record

VenuePlanning Theory · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDemocracyArgument (complex analysis)EpistemologySociologyPoliticsState (computer science)Control (management)Law and economicsPower (physics)Political philosophyLawPolitical scienceEconomicsPhilosophyComputer scienceManagement

Abstract

fetched live from OpenAlex

This article tests the moral limits of autonomous democracy applied to planning theory by offering a critique of the recent work of Mark Purcell. In the first part, I situate Purcell’s view as a pure example of autonomous democracy applied to urban politics and planning. I argue that his view relies on the claim that there is something morally problematic about decision-making in planning that is not exercised autonomously and democratically. Indeed, his approach depends on the claim that autonomous democratic control in planning is morally superior. I consider two arguments for why we might agree. The first is by arguing that indirect centralized (heteronomous) power structures alienate people from their originary state of autonomous control. The second is by arguing that autonomous democracy will lead to the morally best outcomes. Ultimately, I conclude that neither argument works well and that there are not conclusive reasons for thinking that there is something morally better about autonomous democracy as a decision-making structure in planning compared to other forms that don’t rely on direct democratic control.

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)0.013
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.066
Scholarly communication0.0100.010
Open science0.0030.006
Research integrity0.0080.016
Insufficient payload (model declined to judge)0.0030.001

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 head0.090
GPT teacher head0.387
Teacher spread0.297 · 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 designTheoretical or conceptual
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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuePlanning TheorySame topicPolitical Philosophy and EthicsFrench-language works237,207