Bibliographic record
Abstract
Purpose In the past 20 years, doctoral programmes have become the focus of policy initiatives. This has led to considerable changes in their structures and consequently student experience. In this essay, the author explores some of the changes by situating an examination of doctoral education-past, present, future-within the broader context of academic life, and the nature and role of research in developed economies. This analysis provides the context in which to draw out some implications for the future study of doctoral education. Design/methodology/approach The essay draws on a synthesis of the research on doctoral education, early career researcher trajectories, research structures and academic work environment. Findings The analysis suggests the following: doctoral education reform is being driven largely by policy concerns, rather than by evidence or disciplinary intention; and academic work environment is becoming less and less attractive due to increasing demands for productivity and accountability. Originality/value The author concludes with a call to action: unless we, as academics, take action on several fronts, we may find that the PhD becomes purely a policy instrument, and that in the long-term, life of an academic will no longer be attractive to PhD graduates.
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.
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 | 0.060 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.025 | 0.024 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".