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Record W2199438649

Helping Out in the Family Firm: The Legal Treatment of Unpaid Market Labor

2008· article· en· W2199438649 on OpenAlexaffabout
Lisa Philipps

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsYork University
Fundersnot available
KeywordsWifeSpouseUnpaid workWork (physics)SociologyBusinessPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This article investigates the work of individuals who help out informally with a family member's job, often without pay. Examples include the relative who works in the back room of the family business, the executive spouse who hosts corporate functions, the political wife who campaigns with her husband, or the child who does chores on the family farm. The term "unpaid market labor" (UML) is used here to describe the ways that family members collaborate directly in paid activities that are legally and socially attributed to others. The practical legal problems that can arise in relation to UML are illustrated in the context of Canadian and U.S. tax cases regarding the distinction between business and personal activities. The article surveys empirical evidence about the nature and extent of UML undertaken in industrialized countries, and recent studies which suggest that family collaboration in breadwinning may be growing in response to the pressures of economic globalization, technological change, and labor market restructuring. The author proposes a framework for incorporating an analysis of UML into feminist critiques of the market/family dichotomy in law, and responds to possible concerns that doing so may commodify family relations or implicitly devalue unpaid care work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.239
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2008
Admission routes2
Has abstractyes

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