Mobility and International Collaboration: Case of the Mexican Scientific Diaspora
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
We use a data set of Mexican researchers working abroad that are included in the Mexican National System of Researchers (SNI). Our diaspora sample includes 479 researchers, most of them holding postdoctoral positions in mainly seven countries: USA, Great Britain, Germany, France, Spain, Canada and Brazil. Their research output and impact is explored in order to determine their patterns of production, mobility and scientific collaboration as compared with previous studies of the SNI researchers in the periods 1991-2001 and 2003-2009. Our findings confirm that mobility has a strong impact on their international scientific collaboration. We found no substantial influence among the researchers that got their PhD degrees abroad from those trained in Mexican universities. There are significant differences among the areas of knowledge studied: biological sciences, physics and engineering have better production and impact rates than mathematics, geosciences, medicine, agrosciences, chemistry, social sciences and humanities. We found a slight gender difference in research production but Mexican female scientists are underrepresented in our diaspora sample. These findings would have policy implications for the recently established program that will open new academic positions for young Mexican scientists.
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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) | 0.000 | 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 it