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Record W2031247005 · doi:10.1080/15434610600854244

Tensions Within Family Business-Owning Couples Over Time

2006· article· en· W2031247005 on OpenAlexaboutno aff
Sharon M. Danes

Bibliographic record

VenueStress, trauma, and crisis · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsReputationFamily businessEconomic JusticeWork (physics)SociologyPsychologyService (business)State (computer science)ManagementPublic relationsDemographic economicsSocial psychologyMarketingBusinessPolitical scienceEconomicsSocial scienceEngineeringMathematicsLaw

Abstract

fetched live from OpenAlex

The present study examined tensions generated by business issues for 187 family business-owning wives and husbands over a period of time. Family and business goal ranking identified the first priority goal of business owners (husbands) as positive reputation with customers and of wives (household managers) as good family relationships. The tension questions reflect the five conflict content areas of justice, role clarity, work/family balance, identity, and succession. Work/family and justice conflicts were the highest tension producers for both spouses in each time period. About 20% of wives and husbands reported higher work/family conflict in 2000 over 1997. Five out of seven business tensions statistically reduced from 1997 to 2000 for wives; three out of seven statistically reduced for husbands. Family FIRO model is proposed as an assessment and problem-solving model for working with family businesses.

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)0.002
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.012
GPT teacher head0.211
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 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

Citations65
Published2006
Admission routes1
Has abstractyes

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