Mexican Scientist Diaspora in North America: A Perspective on Collaborations With México
Bibliographic record
Abstract
Scientific diasporas from developing countries represent an opportunity to strengthen international collaborations. These collaborations build upon the desire of members of the diasporas to establish scientific, academic, technological, and cultural exchange networks with the communities in their country of origin. While Mexico has a significant number of scientists residing abroad, particularly in North America, and most of them are committed to aid in the country's development, institutional coordination has not harnessed its benefits. In this work, we present an analysis of initiatives carried out by Mexican scientists, members of the diaspora, studying or working in the United States of America and Canada. The study is based on a set of interviews with members of this diaspora. We asked scientists about the conditions that enabled or obstructed their initiatives back in Mexico, and we discussed the role of these factors for capacity building. We also provide general recommendations to enhance contributions to the advancement of science in the country.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.018 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".