The Earth System Governance Project as a network organization: a critical assessment after ten years
Bibliographic record
Abstract
The social sciences have engaged since the late 1980s in international collaborative programmes to study questions of sustainability and global change. This article offers an in-depth analysis of the largest long-standing social-science network in this field: the Earth System Governance Project. Originating as a core project of the former International Human Dimensions Programme on Global Environmental Change, the Earth System Governance Project has matured into a global, self-sustaining research network, with annual conferences, numerous taskforces, research centers, regional research fellow meetings, three book series, an open access flagship journal, and a lively presence in social media. The article critically reviews the experiences of the Earth System Governance network and its integration and interactions with other programmes over the last decade.
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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 | 0.108 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.023 | 0.041 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".