A Multi-disciplinary Mosaic: Reflections on International Security and Global Cooperation
Bibliographic record
Abstract
With contributions by Siddharth Mallavarapu, Lothar Brock, Bernd Lahno, Noemi Gal-Or, Sarah van Beurden, Morgan Brigg, Jan Aart Scholte, Steven Pierce, Abou Jeng, Peter Thiery, Hung-jen Wang, Herbert Wulf, Dong Wang, Jaroslava Gajdošová, Birgit Schwelling, Stephen Brown, Mario Schmidt, Isaline Bergamaschi, Christian Meyer, Mathieu Rousselin, Margret Thalwitz, Gianluca Grimalda, Jessica Schmidt, Marlies Ahlert, and David Chandler. ‘International security’ is a catch-all phrase behind which lie hidden some very disparate assumptions and expectations. One thing on which all may perhaps agree, however, is that such security is only achievable in concert, through global collaboration. Opinions as to which measures of global rapprochement should be given priority vary according to the region and set of assumptions involved. This issue of ‘Global Dialogues’ brings together the reflections of a group of twenty-five scholars on the theme of international security and cooperation.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.022 | 0.037 |
| Scholarly communication | 0.023 | 0.027 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.013 | 0.030 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".