Homecoming After Brexit: Evidence on Academic Migration From Bibliometric Data
Bibliographic record
Abstract
This study assesses the initial effects of the 2016 Brexit referendum on the mobility of academic scholars to and from the United Kingdom (UK). We leverage bibliometric data from millions of Scopus publications to infer changes in the countries of residence of published researchers by the changes in their institutional affiliations over time. We focus on a selected sample of active and internationally mobile researchers whose movements are traceable for every year between 2013 and 2019 and measure the changes in their migration patterns. Although we do not observe a brain drain following Brexit, we find evidence that scholars' mobility patterns changed after Brexit. Among the active researchers in our sample, their probability of leaving the UK increased by approximately 86% if their academic origin (country of first publication) was an EU country. For scholars with a UK academic origin, their post-Brexit probability of leaving the UK decreased by approximately 14%, and their probability of moving (back) to the UK increased by roughly 65%. Our analysis points to a compositional change in the academic origins of the researchers entering and leaving the UK as one of the first impacts of Brexit on the UK and EU academic workforce.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.031 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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; 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".