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Record W4312903091 · doi:10.1561/114.00000033

A Review of <i>Family Business in China</i>

2022· review· en· W4312903091 on OpenAlexaff
Yuying Sun

Bibliographic record

VenueReview of Corporate Finance · 2022
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChinaFamily businessBusinessGeographyBusiness administrationArchaeology

Abstract

fetched live from OpenAlex

Using a sample of 2,000 largest industrial firms in the U.S, we investigate how family involvement influences corporate diversity and whether a governance mechanism – dual-class share structure – moderates this effect. Contrary to typical socioemotional wealth (SEW) predictions, we argue that family firms will tend to engage less in diversity than nonfamily firms due to family firms’ desire to maintain family control and relatively lenient societal pressure on them. We also argue that the adoption of dual-class share arrangement exacerbates family dominance, thus strengthening the negative impact of family involvement on diversity. The results support our arguments and point out the boundary of SEW when involving issues of diversity. We find that family involvement decreases the level of overall diversity, by both engaging less diversity initiatives and causing more diversity-related concerns. Such negative relationship is more pronounced among family firms adopting a dual-class share structure where family owners gain greater control of business. These findings are very robust and provide important theoretical and policy implications.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.013
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.073
GPT teacher head0.292
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2022
Admission routes1
Has abstractyes

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