Bibliographic record
Abstract
This paper explores the evolution of child labour, fertility and human capital in the process of development. In early stages of development, the economy is in a development trap where child labour is abundant, fertility is high and output per capita is low. Technological progress, however, gradually increases the wage differential between parental and child labour, thereby inducing parents to substitute child education for child labour and reduce fertility. The economy takes off to a sustained growth steady-state equilibrium where child labour is abolished and fertility is low. Prohibition of child labour expedites the transition process and generates a Pareto dominating outcome. Child labour is a mass phenomenon in today’s world. According to the ILO Bureau of Statistics, 250 million children aged 5–14 were economically active in 1995, almost a quarter of the children in this age group world-wide. 1 The phenomenon is most widespread in the poorest continent, Africa, but was not always the sole province of the less developed countries: child labour was once common in Europe and in the US, too. In 1851 England and Wales, 36.6% of all boys aged 10–14 and 19.9% of girls in the same age group worked. The historical evidence suggests that child labour has been part of the labour scene since time immemorial. 2 Although the empirical literature on modern-day child labour is abundant, a theoretical examination of the phenomenon is rather scarce. Recent theoretical studies are Basu and Van (1998) and Baland and Robinson (2000). Basu and Van demonstrate the feasibility of multiple equilibria in the labour market: one equilibrium where children work; and another where the adult wage is high and children do not work. Baland and Robinson (2000) study the implications of child labour for welfare. However, despite evidence about the positive relationship between child labour and fertility and a negative effect of income on child labour, existing theories have abstracted from the important dynamic interrelationship between child labour and the process of development. 3
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".