Benefits and geography of international collaboration for PhD students in biology from four global south countries
Bibliographic record
Abstract
Collaboration is a fundamental aspect of scientific research and innovation. Fair collaborations between scientists from different identities or positions of power (e.g., Global North and Global South scientists) could have a great impact on scientific knowledge and exchange. However, there are existing limitations to the potential of Global South scientists to collaborate fairly. Here we assess the impact and geographic distribution of international collaborations for PhD students in biological sciences in four Global South countries (two from Africa: Algeria and Morocco, and two from the Americas: Colombia and Mexico), where students typically have low English proficiency. We show that overall international collaboration, particularly with the Global North, increased the probability of publishing in a journal with an impact factor and achieved more citations. Most international collaborators were affiliated with French-speaking countries for Algerian and Moroccan students and Spanish and English-speaking countries for Colombian and Mexican universities, suggesting that language and geopolitical history might play a role in shaping the selection of international collaborators. While the results highlight the benefit of international collaboration for researchers in the Global South, we discuss that the current metrics of scientific success could maintain the dependence of Global South scientists on the Global North.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.019 | 0.046 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".