Cruising Through School: General Equilibrium Effects of Cruise Ship Arrivals on Employment and Education
Bibliographic record
Abstract
Cruise tourism is the fastest-growing branch of the tourism sector, and many have turned to it as a development strategy despite little systematic evidence of its equilibrium effects. I match 10.6 million automatic identification system (AIS) locations from 517 cruise ships arriving in 265 port destinations to 355,463 Demographic and Health Survey (DHS) women’s surveys in 23 countries to estimate cruise tourism’s relationship with women’s labor market participation and educational attainment. Using fixed effects to identify changes in tourism over time, I estimate that doubling cruise ship arrivals is associated with a 4.9-percentage point increase in labor participation and one-quarter more years of education. These results would be consistent with port cities offering more job opportunities for older women and increased opportunity and available income for education, possibly in anticipation of improved employment prospects. JEL Classifications: D50, I00, J21, O12, Z32
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.003 |
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".