North-South Trade-related Technology Diffusion, Brain Drain and Productivity Growth: Are Small States Different?
Bibliographic record
Abstract
The economies of small developing states tend to be more fragile than those of large ones. This paper examines this issue in a dynamic context by focusing on the impact of the brain drain on North-South trade-related technology diffusion and total factor productivity growth in small and large states in the South. There are three main findings. First, productivity growth increases with North-South trade-related technology diffusion and education and the interaction between the two, and decreases with the brain drain. Second, the impact of North-South trade-related technology diffusion, education, and their interaction on productivity growth in small states is more than three times that for large countries, with the negative impact of the brain drain thus more than three times greater in small than in large states. And third, the greater loss in productivity growth in small states has two brain drain-related causes: a substantially greater sensitivity of productivity growth to the brain drain, and brain drain levels that are more than five times greater in small than in large states.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".