Global public–private partnerships and the new constitutionalism of the refugee regime
Bibliographic record
Abstract
Abstract: Since the early 2000s, regimes and institutions of global governance have undergone a paradigmatic shift in their relations with multinational corporations. The United Nations, in particular, has increasingly embraced big business as ‘partner’ in humanitarian response and development with the establishment of ‘global public–private partnerships’ (GP3s). This article situates this emerging mode of global governance within the recent academic discussions on Global Constitutionalism from a critical political economy perspective, focusing on the case of the UN Refugee Agency’s GP3s in refugee protection and assistance. Critically inquiring into GP3s not only as informal global constitutional arrangements but also as a set of political relations, this article asks: what is the constitutional and political nature of UNHCR–business partnerships? What impacts, if any, do they have on the agency? And, what does this mean for understanding global constitutionalism? The article argues that UNHCR partnerships are constituted as asymmetrical political relations in terms of their distributions of power, benefits, risks and commitments, that they are having neoliberal-oriented constitutive effects on the agency and that these constitutional dynamics challenge the more mainstream and liberal-based conceptualisations, analyses and promotion of current global constitutionalism processes.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.057 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".