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Record W1987851959 · doi:10.7202/1027731ar

Spatialization of political action applied to waterways management an overview of Parisian urban small rivers

2014· article· en· W1987851959 on OpenAlexvenueno aff
Catherine Carré, Jean‐Paul Haghe

Bibliographic record

VenueEnvironnement urbain · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConurbationPoliticsSpatializationEnvironmental planningWater Framework DirectiveRelation (database)Action (physics)Space (punctuation)ObligationEnvironmental resource managementResource (disambiguation)Land useGeographySociologyCivil engineeringPolitical scienceComputer scienceLawEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

The small urban rivers of the Paris conurbation are subject to local land use and segmentation processes at the threshold between urban politics and environmental policy. At present, the obligation to restore these streams pursuant to the Water Framework Directive is challenging stakeholders to proceed as collectively as possibly in this undertaking. This article attempts to identify the points of agreement and disagreement within a shared representation of local decision-makers’ relations with waterways through several spatiotemporal trajectories that are specific to each small river. We will show that the shared management of a river involves the management of not only the resource but also of a shared space. Choosing to model the relation between local societies and their river in time and space around a land-based diagram provides local and regional authorities with an explanation of their interactions with the river and its environments and can foster their capacity to act cohesively.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0020.008
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.293
Teacher spread0.216 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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