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Using a household sampling frame to study family businesses: The 1997 national family business survey

2004· book-chapter· en· W339082570 on OpenAlexaboutno aff
Ramona K. Z. Heck, Cynthia R. Jasper, Kathryn Stafford, Mary Winter, Alma J. Owen

Bibliographic record

VenueAdvances in entrepreneurship, firm emergence, and growth · 2004
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsSampling frameFamily businessFrame (networking)Sampling (signal processing)BusinessMarketingSociologyComputer scienceTelecommunicationsDemography

Abstract

fetched live from OpenAlex

The Family Business Research Group (FBRG) attempts toexplore the relationships between family and business activities within familyfirms by using a household sampling frame (rather than the traditional businesssampling frame). The FBRG is a group of researchers located at 16 U.S. land grantuniversities and the University of Manitoba. The result of the FBRG's effortswas the 1997 National Family Business Survey (NFBS), which required 794households to complete one business and one household interview. The NFBS was designed to analyze the structure, communication patterns,decision-making processes and management strategies in family owned businesses,and included questions on marketing strategies, the customer base and localeconomic viability.This research builds on work previously completed for'At-Home Income Generation: Impact oon Management, Productivity, and Stabilityin Rural-Urban Families,' also called the 'Nine State Study.' The FBRG survey has spawned numerous analyses and studies--e.g., a 1999study that uses the 1997 NFBS data indicates that the average small communitybusiness respondent was 46 years old, white, male, and married.The 1997NFBS challenges conventional notions of family-owned businesses as static andlinear. (SAA)

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)0.001
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 score0.052
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0010.001
Research integrity0.0000.001
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 head0.080
GPT teacher head0.293
Teacher spread0.212 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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