Oral history interview with John Ruggie, 2001
Bibliographic record
Abstract
Background and childhood: born in Graz, Austria, 1944 during time of factionalism, moved to Canada, age 11; education: studies in political science and history at McMaster University, Canada, graduate studies at University of California, Berkeley, 1967; career: consultant to United Nations [UN] on peacekeeping operations, international development, science and technology, and the environment during 1970s, non-governmental [NGO] representative at UN Conference on the Human Environment, 1972, University of California political science professor, 1973, Columbia University political science professor, dean of Columbia's School of International and Public Affairs, 1991-96, professor of international affairs at Harvard University, assistant secretary-general and senior advisor for strategic planning to Kofi Annan, 1997-2001; writings: Multilateralism Matters, Constructing the World Polity, Winning the Peace; themes: Global Compact involvement, globalization, global governance, UN technology use
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".