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Record W4280650722 · doi:10.1080/07053436.2022.2053324

The market of coastal hiking. An approach based on “market-agencements”

2022· article· en· W4280650722 on OpenAlexvenueno aff
Claire Crublet, Élodie Paget

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsCommercializationDestinationsTourismConsumption (sociology)BusinessIndustrial organizationWork (physics)GRASPMarketingEconomic geographyEconomicsGeographyComputer scienceEngineeringSociology

Abstract

fetched live from OpenAlex

The aim of this article is to understand the “market-agencements” deployed around hiking, as pervasive as it is in the tourism offer of French destinations, by focusing on the Breton coastline. On the basis of a socioeconomic market approach as part of the actor-network theory extension, the purpose is to analyze the processes whereby the coastal hiker is transformed into a client, and the commercial relations developing around the commercialized hiking products (from concept to consumption of these goods, via production and commercialization). This perspective helps to grasp the dynamics of the hiking market, the multiplicity of actors engaged in this market, and the role of technical devices in the commercial processes. Based on a qualitative survey, analysis highlights an increasing “economization” of hiking via trails, with a diversified offer of products supported by hybrid networks. The article examines the commercial configurations at work within this multifaceted market.

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)0.002
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 score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.017
Scholarly communication0.0090.013
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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
Published2022
Admission routes1
Has abstractyes

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