Student Needs, Employment Realities, and PhD Program Design in Canada: The Case of Planning PhD Programs
Bibliographic record
Abstract
PhD graduates in Canada routinely find themselves considering employment outside academia. This paper explores PhD program design in relation to PhD students’ employment realities through a case study of Canadian planning PhD programs. Two questions guided the study: (1) How could planning PhD programs be redesigned to prepare students for a wider variety of career options post-graduation? And (2) What are some of the institutional challenges hindering PhD program reform? To engage these questions, we surveyed planning PhD students and program directors, gathered email input from planning practitioners, and held a workshop and roundtable at two different academic conferences. Findings suggest that program reforms, such as offering more external research partnership opportunities to PhD students, could help to better support multiple career pathways for PhD students. Our findings also suggest that planning scholars and practitioners need to question their views of the academia–practice relationship and PhD students’ roles and aims.
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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 | 0.000 | 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) | 0.000 | 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".