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Record W3034814005 · doi:10.1111/joac.12371

Qualifying tradition: Instituted practices in the making of the organic wine market in Languedoc‐Roussillon, France

2020· article· en· W3034814005 on OpenAlexaff
Scott Prudham, Kenneth Iain MacDonald

Bibliographic record

VenueJournal of Agrarian Change · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsWineCommodificationAgrarian societyOrganic productFair tradeEthnographySociologyEconomyMarketingBusinessPolitical scienceGeographyEconomicsLawFood science

Abstract

fetched live from OpenAlex

Abstract Within France, the Languedoc‐Roussillon region (now part of Occitanie) is home to about one third of the nation's area of certified organic vineyards. Each year, the world's largest organic wine fair, Millésime Bio, takes place in the city of Montpellier. This trade fair is an important site where organic wine is not only sold but also given meaning in the market, and importantly, differentiated from but made commensurate with conventional wine. In this paper, we examine processes and practices of ‘qualifying’ organic wine, including by means of relational processes of association and dissociation. Drawing on collaborative event ethnography and other qualitative methods, we focus on individual and institutional actors engaged in creating forms of commodified meanings that circulate with organic wine. In Languedoc‐Roussillon, these meanings reflect and reinforce a longer‐term so‐called shift to quality in wine production, yet also emphasize continuity over change, particularly through emphasis on ongoing role of artisanal, independent growers. We argue that qualification thereby works not only through association with independent growers but also by dissociation, specifically from Languedoc‐Roussillon's agrarian tradition of generic wine production and from the central role played by wine cooperatives in the social reproduction of the region's small‐holding grower class.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.118
GPT teacher head0.281
Teacher spread0.163 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2020
Admission routes1
Has abstractyes

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