Bibliographic record
Abstract
Presents an obituary for John M. Neale. Neale died in Hilton Head, South Carolina, on November 19, 2011, after a long illness. He was born on August 31, 1943, in Toronto, Canada. He received his bachelor's degree from the University of Toronto in 1965, where his interest in psychology had been sparked by an introductory course taught by George Mandler. After working at a residential treatment center for emotionally disturbed children, he decided to pursue graduate training in clinical psychology and enrolled at Vanderbilt University. Rue Cromwell served as John's mentor and stimulated his interest in the investigation of perception and cognition in schizophrenia. His doctorate was awarded in 1969, after completion of his internship at the Langley Porter Neuropsychiatric Institute in San Francisco. John was hired in 1969 as an assistant professor in the new and exciting psychology department (founded in 1965) at the State University of New York at Stony Brook. That department remained his academic home for his entire career. Outside of his academic pursuits, John was an avid New York Giants fan, an extensive traveler, an excellent skier and tennis player, a music lover and jukebox collector, an outstanding cook, a terrific dancer, and a devoted dog owner. He continued to pursue these interests throughout his life, taking cooking classes, traveling to exotic locales with his wife Gail, and, when his health precluded more rigorous athletic pursuits, faithfully walking and playing with his dogs.
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 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.290 | 0.230 |
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".