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Record W2010796818 · doi:10.7202/042874ar

La consultation publique et la question éthique dans les pratiques d'aménagement urbain paysagé. Éléments théoriques et introduction à l'analyse de cas

2005· article· en· W2010796818 on OpenAlexaffvenueabout
Charles Perraton, Irène Cinq-Mars

Bibliographic record

VenueLes Cahiers de droit · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsDemocracyPoliticsMeaning (existential)Relation (database)SociologyPower (physics)Space (punctuation)Participatory democracyPolitical sciencePublic relationsPublic administrationEpistemologyLawComputer scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

With ever-growing concern for democracy, space developers and designers have enlisted public consultation onto their roster of communicational strategies. This strategy coincides with the appearance in our societies of a marked trend towards recognizing individual rights. Among the incidences of consultation may be found that of giving meaning to spaces. Thus these tactics and other practices respond to these strategic efforts that are out of phase with users. What kind of relation with people do these new participatory procedures instate which are based on communicational exchanges of a consultative kind ? In questioning users' "power", it is not so much the political, but rather the ethical question that retains our interest here. Specifically, our objective is to produce creteria enabling the appraisal of the "quality" of programming and designing and that of spatial projects. Our viewpoint is extrapolated results from our research in Les pratiques d'espaces libres urbains à Montréal (FCAR EQ-3013).

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)0.025
metaresearch head score (Gemma)0.022
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 score0.087
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0140.053
Scholarly communication0.0150.011
Open science0.0020.006
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.010
GPT teacher head0.283
Teacher spread0.273 · 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

Citations0
Published2005
Admission routes3
Has abstractyes

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