A global perspective on the social structure of science
Bibliographic record
Abstract
We reconstruct the career-long productivity, impact, (inter)national collaboration, and (inter)national mobility trajectory of 8.2 million scientists worldwide. We study the interrelationships among four well-established bibliometric claims about academics' productivity, collaboration, mobility, and visibility. Scrutinizing these claims is only possible with a global perspective simultaneously considering influential bibliometric variables alongside collaboration among scientists. We use Multiple Correspondence Analysis with a combination of 12 widely-used bibliometric variables. We further analyze the networks of collaboration among these authors in the form of a bipartite co-authorship network and detect densely collaborating communities using Constant Potts Model. We found that the claims of literature on increased productivity, collaboration, and mobility are principally driven by a small fraction of influential scientists (top 10%). We find a hierarchically clustered structure with a small top class, and large middle and bottom classes. Investigating the composition of communities of collaboration networks in terms of these top-to-bottom classes and the academic age distribution shows that those at the top succeed by collaborating with a varying group of authors from other classes and age groups. Nevertheless, they are benefiting disproportionately to a much higher degree from this collaboration and its outcome in form of impact and citations.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".