Bibliographic record
Abstract
After 58 years in science, mostly in pharmacology, one gains perspective. Mine is that there have been important changes over this time, some good and some questionable. In this commentary, I try to reveal how I got to this stage, partially explaining my biases, and possibly helping others learn from my experiences including mistakes. Changing from seeking an M.D. to cellular biology and then to pharmacology early in my career were the best moves I made. The next best move was migration to Canada, away from the McCarthy-McCarran hysteria. Arriving at a time after the end of World War II when science in Canada was expanding was very good luck. I had an excellent opportunity to enjoy both the administration (as Chair of the first independent Department of Pharmacology at the University of Alberta) and the practice of pharmacology (as a practitioner of research on smooth muscle in health and disease). For me, the practice of research has always won over administration when a choice had to be made. Early on, I began to ask questions about educational practices and tried to evaluate them. This led me to initiate changes in laboratories and to seek nondidactic educational approaches such as problem-based learning. I also developed questions about the practice of anonymous peer review. After moving to McMaster in 1975, I was compelled to find a solution for a failed "Pharmacology Program" and eventually developed the first "Smooth Muscle Research Program". Although that was a good solution for the research component, it did not solve the educational needs. This led to the development of "therapeutic problems", which were used to help McMaster medical students educate themselves about applied pharmacology. Now these problems are being used to educate pharmacology honours and graduate students at the University of Alberta. The best part of all these activities is the colleagues and friends that I have interacted with and learned from over the years, and the realization that many of them have collaborated with me again in this volume.
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 | 0.042 | 0.131 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.021 | 0.037 |
| Scholarly communication | 0.015 | 0.025 |
| Open science | 0.010 | 0.011 |
| Research integrity | 0.062 | 0.108 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".