Farewell to the F-word? Fragmentation of international law in times of the COVID-19 pandemic
Bibliographic record
Abstract
The proliferation of international legal regimes, norms, and institutions in the post-Cold War era, known as the ‘fragmentation’ of international law, has sparked extensive debate among jurists. This debate has evolved as a dialectical process, seeing legal scholarship shifting from grave concern about fragmentation’s potentially negative impacts on the international legal order to a more optimistic view of the phenomenon, with recent literature suggesting that the tools needed to contain fragmentation’s ill-effects are today all at hand, thus arguing that the time has come ‘to bid farewell to the f-word.’ Drawing on the COVID-19 crisis as a test case and considering the unresolved problems in existing fragmentation literature that this crisis brings to the fore, this article asks whether such calls have perhaps been premature. Existing works on fragmentation, the article submits, including those bidding farewell to the f-word, have mainly focused on the problems of conflicts between international norms or international institutions, especially conflicts between international courts over competing jurisdictions and interpretations of law. But, as the COVID-19 case – and, particularly, the deficient cooperation marked between the numerous international organizations reacting to the crisis – shows, the fragmentation of the international legal order does not only give rise to the potential consequences of conflicts of norms and clashes between international courts. Fragmentation also gives rise to pressing challenges of coordination when a proactive and cohesive international response is required to address global problems like COVID-19, which cut across multiple international organizations playing critical roles in the creation, administration, and application of international law. By foregrounding cooperation between international organizations as a vital-yet-deficient form of governance under conditions of fragmentation, the article argues, the COVID-19 crisis not only denotes that the time is not yet ripe to bid farewell to the f-word. It further points to the need to expand the fragmentation debate, going beyond its conflict- and court-centred focus, while probing new tools for tackling unsettled problems that arise from the segmentation of international law along sectoral lines.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".