The landscape of public-private partnerships in global health governance: introducing a new dataset
Notice bibliographique
Résumé
BACKGROUND: Global health public-private partnerships are prominent actors and forums for the governance of global health. They channel significant funding into global health and shape policy priorities and options for pressing health problems. Led by state and non-state actors, they are often championed as inclusive governing spaces. Despite their prominence, there is no up-to-date, comprehensive analysis of the quantity and qualities of global health public-private partnerships, including the distribution of decision-making power among their governing board members. RESULTS: This article analyzes a new dataset of 73 global health public-private partnerships governed by a total of 630 actors. These analyses offer three high-level insights. First, high-income country representatives hold 69% of seats on partnership governing boards. Thus, while public-private partnerships have expanded the types of actors that can participate in governance, there remain significant disparities in access to decision-making based on country income-level. Second, a typology of public-private partnerships based on the composition of decision-makers on governing boards is presented. The typology includes Business, Civil Society, Trio, and Super public-private partnerships, of which Trio and Civil Society partnerships are the most common. Third, as public-private partnerships themselves hold governing seats in 24 partnerships, this article lends support to the idea that some partnerships are gaining agency and autonomy in global health through inter-partnership cooperation. Additional analyses shed light on the timeline of the rise of public-private partnerships and a range of characteristics, including their headquarter location, function, health issues addressed, and legal status. CONCLUSIONS: This article provides a big picture perspective on key patterns in the characteristics and distribution of decision-making power of global health public-private partnerships. Together, the analyses suggest that moving from multilateral governance through international organizations like the World Health Organization, to multistakeholder governance through public-private partnerships has contributed to a decrease in decision-making influence for low and middle-income countries and an increase for high-income countries. In doing so, it lays the groundwork for scholarly and practitioner debate about the appropriate distribution of decision-making power in global health governance.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».