Global Public Goods and Democracy in International Legal Scholarship
Bibliographic record
Abstract
Over the last decade, global public goods (GPGs) have been at the centre of the policy discourse of prominent international organisations, States, and non-government organisations (NGOs) alike. The concept emerged in 1999, in a seminal book sponsored by the United Nations Development Programme (UNDP), and finds its origins in economic theory. The economic literature defines public goods as non-rival, since anyone can benefit from them without diminishing the quantity available to other consumers, and non-excludable, as no one can realistically be excluded from their consumption. Nowadays, an increasing number of public goods transcend national boundaries. For instance: climate change mitigation, the eradication of infectious diseases, the fight against corruption, or the protection of the ozone layer are all seen as GPGs. But despite its topicality, the concept has attracted little attention from legal scholars around the globe. Not only this, but among the few authors that actually engage with the topic, the majority focus on issues related to the provision of GPGs, while the question of what goods should be publicly provided in the first place, as well as the decision-making process underlying such a determination, has been left largely unexplored. It is with respect to this specific issue that we wish to contribute to the debate. In our view, the definition of GPGs is a matter of policy choice, as it goes beyond economic, value-free considerations. Therefore, it cannot lie beyond the control of democratic structures. GPGs cannot be defined in a democratic and legal vacuum—a legitimate and inclusive decision-making process is required. In this article, we endeavour to explain how international legal scholarship, in particular the global administrative law and global constitutionalism projects, can contribute to integrating democratic standards in the process of defining GPGs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".