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The University of Arizona.

Measuring Cultural Alignment: Surveys as Cultural Affiliation Networks

Abstract

dc:description.abstract

In recent decades, cultural sociologists have initiated research that brings network-analytic methodologies and relational theorizing to bear on the study of cultural phenomena. I build upon these ideas to study surveys as affiliation networks of persons and the cultural items on which they take positions. Specifically, I conceptualize the qualitative judgments that people make in response to cultural items in surveys as cultural alignments. This dissertation consists of four studies that elaborate my approach to the study of cultural alignment. Although conceptually unified, the empirical substance of these studies ranges broadly across environmental sociology, social networks, social psychology, and the sociology of taste. I discuss two methodological approaches to the study of cultural alignment. The study of individuals’ cultural neighborhoods — referring to an analytically circumscribed and theoretically justified set of cultural position-takings, such as tastes, values, preferences, attitudes, identities, etc. — involves exploiting the principle of duality to characterize individuals’ cultural position-takings in terms of how they correspond to global patterns of position- takings. In contrast, the study of networks of schematic similarity involves conceptualizing inter-individual cultural similarities as social ties. Once constructed, networks of schematic similarity can be analytically reduced to a more easily interpreted dimensional space or split into disparate schematic communities based upon the distribution of edges within the network. Rather than narrowly restricting attention to a circumscribed set of empirical concerns, the studies that comprise the dissertation are instead united by a relational sensibility and, in particular, by a commitment to studying culture through processes of alignment. First, I show how differences in patterns of cultural alignment can be used to explain the relative strength of theorized culture-action relationships. Second, I illustrate that agents translate the empirical properties of their positions within patterns of cultural alignment into the cultural categories they use in everyday boundary-work processes. Finally, I suggest that personal network formation and development are simultaneously processes of cultural alignment, such that individuals organize their relationships in relation to distinctive logics of resource retrieval. I relate the benefits of the cultural-alignment approach to five analytical criteria: (1) formalization of measurement, (2) analytic priority of formal features of culture, (3) a pragmatist semiotic approach, (4) opportunities for endogenous explanation, and (5) validity with respect to cognitive science.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Graduate College
Grantor dc:publisher
The University of Arizona.
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Puetz, Kyle
Advisors dc:contributor.advisor
  • Breiger, Ronald L.
  • Mayer, Brian
Committee member dc:contributor.committeemember
  • Zavisca, Jane R.

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10150/634231
OAI identifier oai:identifier
oai:repository.arizona.edu:10150/634231

Chain of custody

source
Harvested from
University of Arizona
Base URL
repository.arizona.edu/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Puetz, Kyle. Measuring Cultural Alignment: Surveys as Cultural Affiliation Networks. doctoral thesis, The University of Arizona., 2019. http://hdl.handle.net/10150/634231