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Record W2154863611 · doi:10.1177/0170840602231001

The Co-evolution of Institutional Environments and Organizational Strategies: The Rise of Family Business Groups in the ASEAN Region

2002· article· en· W2154863611 on OpenAlexaff
Michael Carney, Éric Gedajlovic

Bibliographic record

VenueOrganization Studies · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsConcordia University
Fundersnot available
KeywordsOpenness to experienceAgency (philosophy)Family businessPath dependenceComplex adaptive systemBusinessSociologyEconomic systemIndustrial organizationEconomic geographyKnowledge managementEconomicsMarketingMicroeconomicsComputer scienceSocial psychologySocial sciencePsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper we consider Southeast Asian Family Business Groups (FBGs) as a form of business enterprise as well as existing theoretical accounts of their behaviour. To do so, we develop and describe a co-evolutionary framework that incorporates notions of interdependence, path dependence, and `system openness.' This co-evolutionary framework is used to anchor a case study describing the developmental paths of FBGs and their institutional environments. Because such neoevolutionary perspectives bring back into account adaptive behavior motivated by human agency and interests, they offer a promising means of capturing the dynamics (Fligstein and Freeland 1995) and complexity (Baum and Singh 1994) of the interaction between institutions and organizations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

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 studies0.0030.003
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.029
GPT teacher head0.229
Teacher spread0.199 · 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 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

Citations262
Published2002
Admission routes1
Has abstractyes

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