Astronomy Research at Canadian Comprehensive Research Universities
Bibliographic record
Abstract
CASCA members at Canadian Comprehensive Research Universities (CCRU) are in a unique situation with respect to research. These institutions are primarily undergraduate, with modest opportunities to supervise graduate students or post-doctoral fellows. Here we outline some of the main challenges faced by researchers at CCRU, as well as some of the, perhaps unexpected, advantages of being at a smaller institution. In writing this article we fully appreciate the difference between research intensive universities and the CCRU universities. However, we strongly believe that CCRU universities are an integral part of the astronomy research landscape in Canada and continue to enable major research breakthroughs while providing notable student experiences. In this sense, perhaps diverging somewhat from perspectives espoused in much Canadian science policy commentary over the last five years, we view institutional diversity as actually a strength of Canadian astronomy rather than a weakness. We state without reservation that students should be accepted into Canadian astronomy from all backgrounds and institutions.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.029 | 0.005 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.047 | 0.005 |
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".