Toward a Global PhD?: Forces and Forms in Doctoral Education Worldwide
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
AcknowledgmentsIntroduction / Maresi Nerad, Thomas Trzyna, and Mimi Heggelund I. Doctoral Education in Europe 1. Germany / Barbara M. Kehm 2. United Kingdom / Howard Green 3. Nordic Countries / Hans Kristjan Gudmundsson 4. The European University Institute / Andreas C. Frijdal 5. The Bologna Process / Jeroen Bartelse and Jeroen Huisman II. Doctoral Education in Africa, South America, and Mexico 6. South Africa / Ahmed Bawa 7. Brazil / Renato Janine Ribeiro 8. Mexico / Armando Alcantara, Salvador Malo, and Mauricio Fortes III. Doctoral Education in Australasia 9. Australia / Terry Evans, Barbara Evans, and Helen Marsh 10. Japan / Shinichi Yamamoto 11. India / Narayana Jayaram IV. Doctoral Education in North America 12. Canada / Garth Williams, with the collaboration of Martha Crago, Jonathan C. Driver, Louis Maheu, and Marc Renaud 13. United States of America / Maresi Nerad Conclusion / Maresi Nerad and Thomas Trzyna Appendix A: Past Differences, Current Commonalities, and Future Trends in Doctoral Education in Selected CountriesAppendix B: Seattle Declaration, September 2005ContributorsIndex
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it