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Contrary to Andreas Behnke's definition of 'manifesto' as stating the manifest, the obvious, there is a tradition of manifesto as a public intervention for the future, an intervention that challenges and displaces what is taken for granted. From the Communist Manifesto to avant-garde manifestos (surrealism, dadaism), from Donna Haraway's Cyborg Manifesto to the contemporary manifesto of anti-capitalist resistance, A Hacker's Manifesto, manifestos have been seen as interventions in the concrete conditions of their time.

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From a complexity perspective on governance, multilateral diplomacy is based on interactions between people, ideas, norms, policies and institutions. This article uses a computer-assisted methodology to better understand governance systems as a network of norms. All World Health Assembly (WHA) resolutions that were available from 1948 to 2022 were collected from the WHO Institutional Repository for Information Sharing (IRIS) database. Regular expressions were used to identify how resolutions cite other resolutions and the resulting relationships were analysed as a normative network. The findings show that WHA resolutions constitute a complex network of interconnected global health issues. This network is characterised by several community patterns. While chain-like patterns are associated with specific diseases programmes, radial patterns are characteristic of highly important procedural decisions that member states reaffirm in similar situations. Finally, densely connected communities correspond to contested topics and emergencies. While these emergeng patterns suggest the relevance of using network analysis to understand global health norms in international organisations, we reflect on how this computational approach can be extended to provide new understandings of how multilateral governance systems work, and to address some important contemporary questions about the effects of regime complexity on global health diplomacy.

This chapter focuses on multiple correspondence analysis (MCA), which is a factor analysis statistical method used to analyse relations between a large set of categorical variables. Developed by Jean-Paul Benzécri in the early 1970s, MCA is one of the principal methods of geometric data analysis (GDA). Three different statistical methods can be identified as GDA: correspondence analysis (CA), which enables the cross-tabulation of two categorical variables; MCA for the analysis of a matrix of individuals and categorical variables; and principal component analysis (PCA), which uses numerical variables. In GDA, data is represented as a cloud of points to allow statistical interpretations. Although MCA is a relational method, it differs from social network analysis (SNA) as it focuses on the objective relations that characterize actors or groups, rather than the effective relations.