Pathways and Mechanisms of Global Cooperation : How Imaginaries Shape Collaboration
Bibliographic record
Abstract
What kinds of processes foster or hinder cooperation over time?What alternative pathways exist that may enable or hinder cooperation on common problems of global scale?What mechanisms foster or hinder global cooperation?How do imaginaries of such pathways shape the process of global cooperation itself?The Centre explores these questions in 2018-2020 from theoretical, empirical and methodological perspectives encompassing research from climate change, peacebuilding, internet, migration governance and other policy fi elds.The research group is coordinated by Senior Research Fellows Katja Freistein and Christine Unrau together with Co-Director Dirk Messner and Director Sigrid Quack.The Centre's research on pathways and mechanisms of global cooperation is motivated by three interrelated developments in global cooperation that have recently stimulated academic interest in the temporal dimension of global governance.Stalemate.Recently we have witnessed re-nationalization moves against multilateral arrangements by state leaders such as Donald Trump and Viktor Orban.To many observers, these withdrawals are only the tip of the iceberg -symptoms of a deeper crisis of multilateralism.While the number of international institutions steadily grew since World War II, this growth has now come to a standstill.Furthermore, the failure to open the United Nations Security Council to include more permanent members illustrates the resistance of international organizations to reform.The perception of 'gridlock' in global governance has stimulated academic interest in processes and mechanisms that could lead us out of the dead-end -alternative pathways of collaboratively acting upon global challenges such as climate change, internet governance or humanitarian relief.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.025 | 0.032 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".