Doctoral Education and the Global University: Student Mobility, Hierarchy, and Canadian Government Policy
Bibliographic record
Abstract
This chapter focuses on (1) the changing role of doctoral education (and the doctoral student) in the context of the global university and (2) the role of government funding policies in these changes. The repositioning of the research university as a central institution within the “knowledge economy,” the increasing use of research outputs as the primary inputs to global rankings, and the complex pressures associated with globalization all suggest major changes in the role and positioning of doctoral education in major research universities. These changes include the rise of Mode 2 knowledge— that is, knowledge produced in collaboration with parties outside the university—in the context of doctoral research, the increased corn-modification of knowledge and education, and a shift in emphasis toward doctoral programs in science and technology. Our analysis of recent policies and trends in Canadian higher education suggests that there are national nuances to these global trends. Doctoral education continues to be defined in national terms, and, given the heavy dependence of doctoral programs on research funds, these programs are influenced by national research policies and funding priorities. We begin this chapter with a historical review of federal government policies related to doctoral education in Canada.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".