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Record W2783443839 · doi:10.1017/jwe.2017.39

Collective Economic Conceptualization of Strategic Actions by Québec Cidermakers: A Mixed Methods–Based Approach

2017· article· en· W2783443839 on OpenAlexaffabout
L. Martin Cloutier, Sébastien Arcand, Éric Michaël Laviolette, Laurent Renard

Bibliographic record

VenueJournal of Wine Economics · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsHEC MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsConceptualizationPerspective (graphical)InferenceAction (physics)Collective actionMicroeconomicsManagement scienceEconomicsSociologyPositive economicsComputer sciencePolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The objective of this article is to estimate the spatial structure of the collective economic conceptualization of strategic actions by cidermakers in Québec. It employs group concept mapping, a mixed methods–based approach. Given the limited research on the economic conceptualization of horizontal coordination for guiding collective strategic action orientations, this contribution is threefold: methodological, empirical, and practical. Methodologically, the results show the perspective of horizontally coordinated cidermakers and use statistical estimates and retroduction as an inference mode to produce and structure the concept map. Empirically, the spatial economic conceptualization consists of a concept map with seven strategic action clusters organized around the notions of product supply and demand and highlights tensions between individual and collective strategic actions. Practically, measures of relative importance and relative feasibility are obtained for each cluster on the map, and implications are discussed. (JEL Classifications: D02, L23, L26, L66, Q18)

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.083
GPT teacher head0.305
Teacher spread0.222 · 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 designNot applicable
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

Citations9
Published2017
Admission routes2
Has abstractyes

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