The Dynamics of Doctoral Candidates and Post-doctorates in Life Sciences in Europe and the United States
Bibliographic record
Abstract
This paper studies the origin and destination of doctoral candidates and post-doctorates in life sciences in Europe, and gives some elements of comparison for the United States, with a combination of three data sources (Eurostat and NetReAct data for Europe, NSF data for the U.S.). We find that the number of doctoral graduates in life sciences in the EU is higher than in the U.S. (9,000 against 6,000) but the proportion of foreigners is lower in the EU (17% against 29%). The number of postdoctorates in life sciences is more or less the same in the EU and the U.S. (19,000 against 18,000) but the EU attracts less foreign postdoctorates than the U.S. (25% against 57%). 76% of doctoral graduates in life sciences from EU universities continue to work in the EU after graduation whereas 12% go to the U.S. or Canada, and another 12% go to another country. For postdoctorates from EU universities, percentages are more or less the same (76% stay in the EU, 8% go to the U.S. or Canada and 16% to another country).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".