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Record W2043387095 · doi:10.7202/1024807ar

Les nouveaux territoires du surf dans la ville

2014· article· fr· W2043387095 on OpenAlexaff
Sylvain Lefèbvre, Romain Roult

Bibliographic record

VenueTéoros Revue de recherche en tourisme · 2014
Typearticle
Languagefr
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

La culture surf qui a tant marqué la côte ouest américaine à partir des années 1950, culture qui s’est mondialisée et commercialisée avec plusieurs tendances toutes aussi variées et inusitées les unes que les autres, a créé un univers aux proportions imposantes dans les dix dernières années. L’industrie du divertissement, du sport et du loisir est au centre de cette révolution, mais aussi celle du vêtement, de la mode et d’autres produits dérivés. Plus significatif encore, le surf original a influencé plusieurs pratiques sportives tant sur l’eau que sur terre ou sur neige, et désormais les intervenants touristiques de même que ceux en aménagement du territoire doivent s’adapter et composer avec ces nouvelles réalités. L’article dressera un panorama de cette constellation d’activités, qui ont le surf comme point de départ, et de leurs évolutions récentes. Puis, plus spécifiquement, il sera question des impacts de ces activités sur l’espace urbain à travers des modes d’appropriation de territoires en apparence plutôt inadaptés aux « sports de glisse ».

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)0.001
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.007
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.088
GPT teacher head0.374
Teacher spread0.286 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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