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Record W2016331529 · doi:10.1080/07053436.2014.881092

Renouveler l’identité de la ville entre culture portuaire et loisirs. Le cas de Livourne

2014· article· fr· W2016331529 on OpenAlexvenueno aff
Laura Verdelli, Francesca Morucci

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2014
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationPort (circuit theory)PremisePoliticsTourismTheme (computing)Urban planningFellPolitical scienceEconomyGeographyArchaeologyCivil engineeringEngineeringCartographyEconomicsLaw

Abstract

fetched live from OpenAlex

The theme of cities developed for leisure is illustrated with the example of port cities, which constitute a unique urban layout. Economic, urban and socio-political changes in the last 30 years have led to a rethinking of the urban and territorial configuration. Thus, large abandoned parts of ports have hosted operations for new recreational areas on the waterfront, amenities offering new perspectives on the harbor, boating facilities, enhancement of the port and industrial heritage… This article starts from the premise that the first wave of revitalization of many neglected port areas first fell into a logic of urban renewal exclusively through leisure, and then, by means of intermediate phases, these projects have evolved, over the past two decades, to projects led by new ambition, closer to the city and its inhabitants, combining culture and recreation.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.027
Scholarly communication0.0150.011
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.016
GPT teacher head0.291
Teacher spread0.275 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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