Migration, Trade, and Development
Bibliographic record
Abstract
"Migration and trade are more prevalent today than ever before in the history of the world. The United States is the recipient of about one-third of the world’s migrants and accounted for a quarter of the world’s output and 13 percent of the world’s trade in 2005. But the global significance of the U.S. economy is slowly declining, and while the effects of migration and trade on the U.S. economy have been examined time and again, questions concerning the impact of migration and trade on development in low-income countries are of growing importance. Simple, neoclassical economic models predict that prices should drive factors such as labor and capital across regions and countries toward their most valuable use. As this happens, developing countries, which are typically labor-rich and capital-scarce, should experience more rapid growth, higher income, and eventually convergence to industrial world levels of well-being. This process is happening slowly in some cases, but in other cases not at all. Do migration and trade speed this convergence? If so, how? If not, why? These questions are addressed from different perspectives in the following papers presented at the conference “Migration, Trade, and Development,” held in Dallas in October 2006."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".