Bibliographic record
Abstract
David Lotto was born as the elder of two sons on December 18, 1946 in Manhattan to first generation Jewish-American parents whose parents came from Eastern Europe. His father worked several jobs, including as an x-ray technician, as well as a salesman of home products, cemetery plots, and mutual funds before working for the New York City Housing Authority. His mother, meanwhile, worked as a homemaker and secretary and later as an elementary school teacher in New York City public schools. The family moved to the Bronx when he was five, and he graduated from the Bronx High School of Science at age 16. In 1967 David graduated from Brandeis University with a double major in physics and psychology as well as a minor in the philosophy of science. He then entered the clinical psychology graduate program at the University of Chicago in 1967, where he connected with David Bakan who was interviewed by Clio’s Psyche as a featured scholar in our September 1998 issue. After President Richard Nixon ended graduate school deferments for the Vietnam War, he and Bakan went to York University in Toronto, where he received his master’s degree in 1969 and doctoral degree in psychology in 1974.
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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.028 | 0.015 |
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".