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Record W2114991934 · doi:10.1509/jm.13.0280

Ideological Challenges to Changing Strategic Orientation in Commodity Agriculture

2014· article· en· W2114991934 on OpenAlexaff
Melea Press, Eric J. Arnould, Jeff B. Murray, Katherine Strand

Bibliographic record

VenueJournal of Marketing · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsMcGill University
Fundersnot available
KeywordsIdeologyCommodityIncentiveLegitimacyContext (archaeology)BusinessPerspective (graphical)MarketingMarket economySociologyEconomic systemEconomicsPublic relationsPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Why do some firms not change their strategic orientation despite economic incentives to do so? Most current literature on changing strategic orientations has focused on an antecedents and outcomes approach to business orientations. Intimated, but rarely addressed, are the notions that (1) strategic orientations may be thought of as ideologies and (2) such ideologies are likely to contend with each other. Taking such a perspective may be helpful in discussing why it is challenging to transition to more sustainable strategic orientations even in the presence of financial incentives to do so. In assessing the transition to organic production and marketing in a commodity agriculture context, the authors find that contending ideologies restrict its adoption. In addition, they suggest that strategic orientations are not adopted or contested solely within firms but also among them. The authors find that ideological contestation among firms in this context takes the form of a marketplace drama between a chemical, productionist orientation and an organic orientation in which protagonists mobilize several forms of legitimacy.

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)0.008
metaresearch head score (Gemma)0.012
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.016
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.269
Teacher spread0.234 · 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

Citations77
Published2014
Admission routes1
Has abstractyes

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