Multifractal signatures of intersectionality: nonlinear dynamics permits quantitative modeling of hierarchical patterns in gender dynamics at the cultural level

Hannah L. Brown, Chase R. Booth, Elizabeth G. Eason and Assistant Professor Damian G. Kelty-Stephen

Chapter 13 in Handbook of Research Methods in Complexity Science, 2018, pp 254-266 from Edward Elgar Publishing

Abstract: This gender study exemplifies fields struggling to balance the deeply ingrained desire for logical formalisms and conceptually dynamic models of systems. Gender Studies grounds itself in dynamic models as seen in the popularity of ‘intersectionality theory,’ a notion of experiences as unfolding at the ‘intersections’ of classical taxonomies. This popular theory evades quantitative research because it eschews classical categorical distinctions. The authors introduce multifractal analysis and suggest that cascade dynamics and multifractal analysis provide logical and corresponding statistical frameworks to make intersectionality quantitatively and tractably expressible for gendered experiences. Recent cognitive science advances involve multifractal analysis laying bare key features of the cascades driving cognitive performance. The chapter offers similar demonstration of similar cascades in gender dynamics through multifractal analysis of web-traffic data for gender terms on Wikipedia. It concludes that cascade formalisms and multifractal analysis offer new avenues for gender studies balancing both logical formalisms and dynamic concepts.

Keywords: Business and Management; Geography; Innovations and Technology; Politics and Public Policy Research Methods; Urban and Regional Studies (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.elgaronline.com/view/9781785364419.00024.xml (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:elg:eechap:16937_13

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this chapter

More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().