Mapping academic migration of German-affiliated researchers across countries using 8 million Scopus publications from 1996 to 2020
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Academic mobility plays a predominant role in the context of increasing the internationalization of science and research production, thus creating a global market of qualified professionals Germany has launched a series of programs that have the aim to attract researchers with high citation performance and link German-affiliated scientists abroad with each other (Schiller and Cordes, 2016). Thus, mapping the German academic in-and out-flow patterns across countries and disciplines can help clarify the position and attraction of Germany in the global science system. Taking all fields of scholarship, this analysis speaks directly to policy development. Using large-scale bibliometric data from over 8 million Scopus publications during the period 1996-2020, we analyze and visualize the international migration to and from Germany among published researchers by taking into account their citation information and semantically identified disciplines. This reveals the spatial hotspots of migration and in-and out-flows for all fields of scholarship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.090 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 it