PhD students’ excellence scholarships and their relationship with research productivity, scientific impact, and degree completion
Bibliographic record
Abstract
This paper examines the relationship between excellence scholarships and research productivity, scientific impact, and degree completion. Drawing on the entire population of doctoral students in the province of Québec, this paper analyzes three distinct sources of data: students, excellence scholarships, and scientific publications. It shows that funded students publish more papers than their unfunded colleagues, but that there is only a slight difference between funded and unfunded PhD students in terms of scientific impact. Funded students, especially those funded by the federal government, are also more likely to graduate. Finally, although funding is clearly linked to higher degree completion for students who did not publish, this is not true of those who managed to publish at least one paper during the course of their PhD. The paper concludes with a discussion of the implication of the findings for Canadian science policy.
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 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 | 0.022 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.030 | 0.036 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".