The Distributional and Allocative Impacts of Virtual Labor Mobility across Time Zones through Communication Networks
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Using a specific‐factors' model, with two goods (a shift‐working good and a non‐shift‐working good), three factors (capital specific to shift‐working, land specific to non‐shift‐working and labor) and two countries (Home and Foreign), which are located in different time zones, we highlight the impact of trade in labor services via communication networks on factor prices and production patterns. If two countries are identical in size, then under free trade in labor services, all workers work only in their local daytime, and night shift in each country is performed by imported labor services supplied by residents of the other country in their local daytime. Night‐time wage becomes the same as daytime wage (a wage equalization result). Other factor prices are also equalized. In both countries, capital rental rate increases, while land rent decreases. However, if two countries are different in size, trade in labor services does not equalize wages: in the large country, wages for night‐shift workers are higher than daytime wages and some residents work at night; in the small country, daytime wages become higher than night‐time wages and no one works at night, and night‐shift work is done by imported labor services from the large country. Land rent in the small country decreases. Land rent in the large country may or may not decrease, but it is always higher than in the small country. Capital rental rates in both countries are equalized and increase.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it