Bibliographic record
Abstract
Presents an obituary for Herbert M. Lefcourt. In the summer of 1963, with a freshly minted PhD degree in his hands, Lefcourt moved to Waterloo, Ontario, Canada. Along with several other young faculty members from the United States, Herb had been recruited to help establish a new PhD program in clinical psychology at the University of Waterloo. Over the ensuing years, it became recognized as one of the leading clinical programs in North America. Ever an optimist with a zest for life, Herb focused on the positive side of human nature in his research interests. While others studied stress and distress, Herb was more interested in the personality traits of people who are particularly resilient, able to withstand adversity without succumbing to illness and depression. Later in his career, his interests turned to the study of the sense of humor, again conceptualized as a personality variable with important implications for mental and physical health. Herb retired from the university in 1996 and was awarded the honorific of Distinguished Professor Emeritus. He had a very enjoyable retirement, pursuing his many interests, which included international travel, hiking, woodworking, literature, film, and classical music, and enjoying his summer cottage on Manitoulin Island in Lake Huron. He is remembered as an energetic teacher who, in addition to having an eclectic command of the theory and research, drew on his vast knowledge of literature, film, and current events to make his lectures interesting, informative, and thought-provoking.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.202 | 0.155 |
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".