Alternative and professional doctoral programs: what is driving the demand?
Bibliographic record
Abstract
As part of an overall massification of higher education, enrollments in doctoral programs are expanding. At the same time, doctoral studies are subject to much scrutiny and reform in Australia, the UK and the United States. This work examines policy documents related to doctoral reform from these countries in order to offer a critique of their functionalist underpinnings. Central to doctoral reforms is the growth of the professional doctorate, which is proposed as an alternative to conventional PhDs that better prepares graduates to participate in non‐academic careers. In this work, the professional doctorate is examined from the dominant perspective of human capital theory. Alternative theories emphasizing conflict and competition in higher education are offered. Credentialism and the corporatization of higher education may provide more nuanced explanations of the growth of the professional doctorate. The article concludes with some thoughts on the impacts of policy on those whose lives are ultimately shaped by it: students and graduates who may be disappointed to find that human capital theory does not deliver on its promise of status and prosperity for society’s most highly educated workers.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".