The Pugwash scientists’ conferences, Cyrus Eaton and the clash of internationalisms, 1954–1961
Bibliographic record
Abstract
This paper examines the contest between Canadian American industrialist Cyrus Eaton and the Pugwash scientists' leadership for influence over the early Pugwash scientists' conferences. Eaton's activism has generally been dismissed in the historical literature as ineffective, naive and too uncritical of the Soviet Union. This paper argues that he was genuinely committed to international peace and security, that Eaton shared with Pugwash scientists a belief in the importance of intellectuals to global unity, and that he worked to bring about greater international peace and understanding through both his personal activism and his own conferences held in the town of Pugwash. Eaton, however, favoured a broader push for peace, which included participation by a wider range of intellectuals and a call for rapprochement with the Soviet Union. These differences between Eaton and the Pugwash scientists, I argue, were more than simply about approach: they represented different internationalist visions and manifested in different conceptualizations for the Pugwash scientists' conferences. Eaton hoped to incorporate non-scientists and humanism into the conferences, and integrate them into his own broader conference programme at his Thinkers' Lodge at Pugwash. The scientists, however, wanted to keep their conferences as distinctly scientists' events, tied to science and its authority.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".