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Record W1490210444

Endogenous Technical Progress and the Emergence of Child Labor Laws

2003· preprint· en· W1490210444 on OpenAlexaff
Sylvain Dessy

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsOpposition (politics)Labour economicsEconomicsThe labor problemHuman capitalLabour lawLabor demandLabor relationsPoliticsMarket economyPolitical scienceLawWage
DOInot available

Abstract

fetched live from OpenAlex

I develop a theory of technical progress that uncovers sufficient conditions for opposition to the adoption of child labor laws to disappear over time. The supply of child labor comes exclusively from unskilled parents, because of their inability to help their children benefit from formal education, while its demand originates from capitalists-the firms' owners. Because child labor crowds out adult employment, there are always social pressures to ban it. However, such pressures are met by capitalists' opposition. Capitalist oppose the adoption of a ban on child labor because such a ban reduces opportunities for earning a high return on capital. Technical progress, induced by skill accumulation, improves the earning prospects of firms hiring adult workers only, while it reduces those of firms hiring children only. As a result, more capitalists are drawn into the adult labor market, and industrial opposition to a ban on child labor eventually vanishes over time. Provided child labor exhibits skill-enhancing learning-by-doing, policy action to speed up the emergence of child labor laws should therefore focus on education reforms that raise the quality of education school-goers receive, and on political reforms that raise the cost of lobbying legislators against adopting a ban on child labor. However, in countries where child labor provides little or no opportunities for learning-by-doing, no law will emerge unless appropriately targeted poverty alleviation mechanisms are designed, in order to induce unskilled parents to allocate a positive fraction of child's time to schooling.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.029
GPT teacher head0.329
Teacher spread0.300 · 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 designTheoretical or conceptual
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

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicPoverty, Education, and Child WelfareFrench-language works237,207