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Dynamiques de participation communautaire dans la gestion d’installations publiques. Deux cas d’étude à Barcelone

2020· article· fr· W3012263086 on OpenAlexvenueno aff
Santiago Eizaguirre Anglada

Bibliographic record

VenueInterventions économiques · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article explore les différences entre deux projets visant à promouvoir la culture de proximité et le développement territorial à Barcelone. Sont analysées les différences entre deux manières de gérer des équipements municipaux ayant pour but de favoriser la création et la participation citoyenne. Il s’agit de deux cas situés dans deux quartiers aux profils socioéconomiques diamétralement opposés : un Fab Lab à Ciutat Meridiana et le centre civique Casa Orlandai à Sarrià. Dans le premier cas, les dirigeants du secteur public ont été confrontés à l’acceptabilité du tissu associatif local et ont dû progressivement développer des activités plus en adéquation avec les besoins du quartier. Dans le deuxième cas, une plate-forme citoyenne a favorisé l’implication du public dans le développement d’un projet à vocation sociale. La comparaison des cas montre que les facteurs structurels affectent directement le démarrage de ce type d’initiatives. Le souci de coresponsabilité de la communauté et de la municipalité dans les tâches de gestion apparaît comme un défi commun.

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)0.006
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.078
GPT teacher head0.360
Teacher spread0.282 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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