Global forms and local forces : PhD enrollments and graduations in Australia, Canada, the Czech Republic, the United Kingdom, and the United States
Bibliographic record
Abstract
\n\t\t\t\t\t This chapter presents and discusses data from five different nations—Australia, Canada, the Czech Republic, the United Kingdom, and the United States—on doctoral candidates and graduates. These data are from governmental and institutional sources for the years 1998–2004, a sample that enables changes across a five-year span to be identified. They span important basic characteristics, such as gender, age, discipline, and study load (that is, full-time or part-time study). Therefore, readers can see national as well as international trends and differences in such characteristics and can match these to equivalent and/or contemporary data in their own nations. The five countries considered here are among those whose data were discussed at the 2007 CIRGE research synthesis meeting in Australia. Although these countries are not universally representative of doctoral education, their practices do offer a vivid sense of how vastly the enterprise of doctoral education differs in its scope and dimensions around the world\n\t\t\t\t
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".