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Record W3193848719 · doi:10.6000/1929-4409.2021.10.149

Cooperative Strategic Entrepreneurship: A Case Study from Indonesia

2021· article· en· W3193848719 on OpenAlexvenueno aff
Mochamad Heru Riza Chakim, Erna Maulina, Margo Purnomo, Anang Muftiadi, Achsanul Qosasi

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipVariable (mathematics)Relevance (law)Interpretation (philosophy)BusinessMarketingStrategic managementStrategic ChoicePublic relationsIndustrial organizationPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This article offers an in-depth case study of the relevance of dairy cow milk cooperatives in Indonesia that align with the concept of strategic entrepreneurship in social benefit practices. An advocacy lens based on the strategic entrepreneurship model is used by making comparisons of the constructs that form strategic entrepreneurship to bridge a practical understanding of cooperatives with local cultural backgrounds. Descriptive analysis is used to report interrelated themes in the case study of cooperative organizations and finally interpretation. An interesting finding is based on the research results, that is, the wealth creation of an organization is not the final model variable, but a social benefit variable, which then becomes a cycle of environmental resources. Cooperatives realize that personal benefits are not a sub-variable of constructing goals. This research describes the dynamics of the opening of the concept of strategic entrepreneurship in cooperative companies that consider new social risks and benefits.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.002
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 head0.079
GPT teacher head0.314
Teacher spread0.235 · 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
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Criminology and SociologySame topicEntrepreneurship Studies and InfluencesFrench-language works237,207