A Transparent Neural Architecture Reveals The Structure and Variability of Ideological Organization Across Societies

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dc.contributor.advisorCandia Vallejo, Cristian
dc.contributor.authorFuentes Jofré, Adolfo Ignacio
dc.coverage.spatialSantiago
dc.date.accessioned2026-08-03T21:55:23Z
dc.date.available2026-08-03T21:55:23Z
dc.date.issued2026
dc.descriptionA dissertation submitted to the Faculty of Government at the Universidad del Desarrollo in partial fulfillment of the requirements for the degree of Doctor in Social Complexity Science
dc.description.abstractPolarization is often described as a defining feature of contemporary politics, yet most evidence comes from political elites or from studies focused on the United States. The structure of citizens’ ideological preferences, and how it varies across societies, remains poorly understood. We present DYNAMAP, a transparent neural framework that infers the latent geometry of human value organization directly from behavioural data. By embedding individuals and policy options in a shared space based on pairwise comparisons among real public policy issues, the model captures how citizens balance competing political values without relying on self-reports or elite cues. Applied to revealed-preference datasets from Chile, France, and Brazil, three contrasting political contexts, DYNAMAP identifies a shared, low-dimensional ideological structure anchored by a left–right axis and a secondary component reflecting contextual diversity. Within this common geometry, polarization follows distinct trajectories: among younger generations it intensifies in France and Brazil but weakens in Chile, driven by moderation among younger right-leaning participants. Traditional approaches based on self-declared ideology provide limited insight into how citizens actually organize competing values. Given that DYNAMAP learns ideological structure directly from behavioural comparisons, it reveals context-specific generational patterns that remain obscured in conventional survey data. These findings suggest that polarization reflects context-dependent rearrangements within a stable ideological space, offering a scalable and interpretable approach for understanding how societies organize disagreement.
dc.format.extent90 p.
dc.identifier.urihttps://hdl.handle.net/11447/10948
dc.language.isoen
dc.publisherUniversidad del Desarrollo. Facultad de Gobierno
dc.subjectPolarización política
dc.subjectPreferencias reveladas
dc.subjectIdeología
dc.subjectAprendizaje automático
dc.subjectComparaciones pareadas
dc.subjectPolitical polarization
dc.subjectRevealed preferences
dc.subjectIdeology
dc.subjectMachine learning
dc.subjectPairwise comparisons
dc.titleA Transparent Neural Architecture Reveals The Structure and Variability of Ideological Organization Across Societies
dc.typeThesis
dcterms.accessRightsPrivado

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