Brain Drain or Brain Bank? The Impact of Skilled Emigration on Poor-Country Innovation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The development prospects of a poor country depend in part on its capacity for innovation. The productivity of its innovators depends in turn on their access to technological knowledge. The emigration of highly skilled individuals weakens local knowledge networks (brain drain), but may also help remaining innovators access valuable knowledge accumulated abroad (brain bank). We develop a model in which the size of the optimal innovator diaspora depends on the competing strengths of co-location and diaspora effects for accessing knowledge. Then, using patent citation data associated with inventions from India, we estimate the key co-location and diaspora parameters; the net effect of innovator emigration is to harm domestic knowledge access, on average. However, knowledge access conferred by the diaspora is particularly valuable in the production of India's most important inventions as measured by citations received. Thus, our findings imply that the optimal emigration level may depend, at least partly, on the relative value resulting from the most cited compared to average inventions.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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