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Record W3016138707 · doi:10.1108/jfbm-01-2020-0003

Entrepreneurial families in business across generations, contexts and cultures

2020· article· en· W3016138707 on OpenAlexaff
Albert E. James, Εlias Hadjielias, Maribel Guerrero, Allan Discua Cruz, Rodrigo Basco

Bibliographic record

VenueJournal of Family Business Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRelevance (law)OriginalityContext (archaeology)Family businessPerspective (graphical)EntrepreneurshipValue (mathematics)SociologyPhenomenonBusiness modelConceptual frameworkPublic relationsMarketingKnowledge managementBusinessSocial sciencePolitical scienceEpistemologyQualitative researchComputer science

Abstract

fetched live from OpenAlex

Purpose This article is the editorial for the special issue on “Entrepreneurial Families in Business Across Generations, Contexts and Cultures”. We aim to develop a road map that can help academics and practitioners navigate the findings of the articles contained in this special issue. We also suggest future lines of research around the topic of entrepreneurial families in business. Design/methodology/approach We develop a conceptual model for interpreting and understanding entrepreneurial families in business across contexts and time. Findings Our conceptual model highlights the importance of context and time when conducting research on entrepreneurial families in business. Practical implications The findings in this special issue will be of relevance for decision makers who tailor policies that embrace different economic and social actors, including entrepreneurial families. Originality/value This editorial and the articles that make up this special issue contribute to family business research by contextualising the phenomenon of entrepreneurial families in business. We propose a new holistic perspective to incorporate context and time in the study of entrepreneurial families that own, govern and manage family firms over time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.021
GPT teacher head0.256
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 teacher head, not a consensus.

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

Citations62
Published2020
Admission routes1
Has abstractyes

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