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Record W2714880431 · doi:10.1177/0894486517715838

The Impact of Adolescent Work in Family Business on Child–Parent Relationships and Psychological Well-Being

2017· article· en· W2714880431 on OpenAlexafffundabout
Marjan Houshmand, Marc‐David L. Seidel, Gary Dennis

Bibliographic record

VenueFamily Business Review · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPsychologyNational Longitudinal SurveysWork (physics)Longitudinal dataQuality (philosophy)Regression analysisLongitudinal studySurvey data collectionDevelopmental psychologySocial psychologyDemographic economicsSociologyDemographyMedicineEconomics

Abstract

fetched live from OpenAlex

Previous ecological theory of human development research shows mixed results concerning the impact of adolescent work on psychological and family outcomes. We show the consequences of working in the family firm on adolescents’ parental relationships, self-esteem, and depression, highlighting the importance of high-quality work experiences in the early life course. Weighted regression analysis of longitudinal data from Statistics Canada’s National Longitudinal Survey of Children and Youth shows that those adolescents who work in their family firms on a year-round basis report a better relationship with their parents, and better psychological well-being than their nonfamily firm working counterparts.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.077
GPT teacher head0.323
Teacher spread0.246 · 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 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

Citations32
Published2017
Admission routes3
Has abstractyes

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