MétaCan
Menu
Back to cohort
Record W2993977601 · doi:10.1177/0894486519893223

Managing Family-Related Conflicts in Family Businesses: A Review and Research Agenda

2019· review· en· W2993977601 on OpenAlex
Qiu Hong, Mark Freel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFamily Business Review · 2019
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFamily businessDialecticPopularityIntervention (counseling)Public relationsFamily conflictWork–family conflictBusinessWork (physics)Social psychologyMarketingPolitical sciencePsychology

Abstract

fetched live from OpenAlex

This review examines how family businesses manage family-related conflicts that occur at three interfaces: family-business, family-ownership, and family-business-ownership. We find that work-family conflicts, conflicts of interest, and relationship conflicts are prevalent family-related conflicts. Four conflict management strategies are frequently used to deal with these conflicts: vacillation, domination, separation, and third-party intervention. The popularity of these strategies is influenced by some unique characteristics of family businesses, such as high emotional attachment among family members. By integrating insights from the broader conflict research, paradox and dialectic studies, we develop a research agenda targeted at better connecting family-related conflicts to conflict management strategies.

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.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.546
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0040.020
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.006

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 head0.176
GPT teacher head0.384
Teacher spread0.208 · 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