Discussion Paper Series The Wages of Sin
Bibliographic record
Abstract
Edlund and Korn [2002] (EK) proposed that prostitutes are well paid and that the wage premium reflects foregone marriage market opportunities. However, studies of street prostitution in the U.S. have revealed only modest wages and considerable risks of disease and violence, casting doubt on EK’s premise of an unexplained wage premium. In this paper, we present evidence from high-end prostitution, the so called escort market, a market that is, if not entirely safe, notably safer than street prostitution. Analyzing wage information on more than 40,000 escorts in the U.S. and Canada collected from a web site, we find strong support for EK. First, escorts in the sample earn high wages, on average $280/hour. Second, while looks decline monotonically with age, wages follow a hump-shaped pattern, with a peak in the 26-30 age bracket, which coincides with the most intensive marriage ages for women in the U.S. Third, the age-wage profile is significantly flatter, and prices are lower (5%), despite slightly better escort characteristics, in cities that rank high in terms of conferences, suggesting that servicing men in transit is associated with less stigma. Fourth, this hump in the age-wage profile is absent among escorts for whom the marriage market penalty is lower or absent: escorts who do not provide sex and transsexuals.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.214 | 0.036 |
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".