Oral history interview with David Z. Robinson 1998
Bibliographic record
Abstract
Childhood: Montreal; Harvard University: A.B., 1946, A.M., 1947, Ph.D. Chemical Physics, 1949; Americans for Democratic Action, Vice President of Cambridge chapter; Assistant Director for Research Study, Baird Associates, 1949-1959; Office for Naval Research, London, 1959-1960; member of the Optical Society to the International Commission for Optics; Office of the Scientific Advisor to the President, Science Advisory Committee, Communications Satellite Act, Air Traffic Control, White House-Kremlin hotline, liaison to the Ramsey Panel, liaison to National Science Foundation, 1961-1967; Vice President for Academic Affairs, New York University, student activities during Vietnam War era, 1967-1970; Vice President, Carnegie Corporation, Carnegie Foundation for the Advancement of Teaching, 1970-1980; Board of Trustees of City University of New York, 1976-1981; Executive Vice President of Carnegie Corporation, 1981-1985; Executive V.P. Treasurer, Carnegie Corporation, 1988-1997; Director, Carnegie Commission on Science, Technology, Government, 1988-1997; panel member, President's Science Advisory Committee on Hijacking; member, Naval Research Advisory Committee; member, Governor Hugh Carey's Task Force of Higher Education; reminiscences of colleagues.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.186 | 0.065 |
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".