Promoting International Scientific Cooperation: the Role of Scientific Societies
Bibliographic record
Abstract
Abstract Scientific collaboration yields many advantages, especially in fields that require interdisciplinary approaches, as it fosters the sharing of knowledge and resources and is essential for the implementation of complex projects. The concept of scientific internationalism emerged around the 1900s, emphasizing that science surpasses national boundaries and promotes global peace and collaboration. International scientific cooperation is halted by geopolitical tensions and conflicts, such as World War II and the Cold War. Nevertheless, many examples show that scientific collaboration can surpass conflicts and bring scientific and society development, such as in the cases of the Tick-borne Encephalitis vaccine, the Apollo-Soyuz test project and more recently the international endeavour for COVID-19 vaccine development. In this contest, UN and WHO have an imporant role to promote peace and scientific cooperation, examplified by the 16th Sustainable Development Goal, to “Promote just, peaceful and inclusive societies”. This review aims to assess the available literature regarding international scientific collaboration and the role of scientific societies in promoting scientific cooperation. Scientific societies have proved to be pivotal in bridging cultures and promoting international cooperation. Apart from the historical example of the International Institute for Applied Systems Analysis, which showed an important cooperation between Western and Eastern countries during the Cold War, the scientific society European Biotechnology thematic network Association (EBTNA) has international scientific cooperation as one of its critical goals. Scientific societies such as EBTNA will be pivotal in promoting international scientific cooperation and fostering international activities and scientific research.
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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 | 0.028 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".