Bibliographic record
Abstract
This chapter assesses long term changes in the within-factor income distribution, focusing on changes in the distribution of urban formal sector wages. Specifically, it argues that urban formal sector wage inequality has been relatively modest in many Latin American countries (LACs) until, at least, the 1970's. The chapter adopts an international comparative perspective, including the US, Canada and Australia to highlight the specific 'Latin' features of the long run trend in urban wage inequality. It analyses some detailed early 20th century wage distribution surveys in Argentina, showing that urban wage inequality was indeed modest compared to international standards. It also examines the long run trends in the distribution of manufacturing wage income in a Theil-index framework. Finally, the chapter discusses a number of hypotheses to explain the recent rise in urban wage inequality, placing the events of the last quarter of the 20th century in an integrative historical context.Keywords: Latin American countries (LACs); Theil-index framework; urban wage inequality; wage distribution surveys; within-factor income distribution
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".