Multiples Over Models

Author:

Fox Sarah E.1,Menking Amanda2,Eschler Jordan3,Backonja Uba4ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA

2. University of Washington, Seattle, WA

3. Northwestern University, Chicago, IL

4. University of Washington, Tacoma, WA

Abstract

In this article, we describe our efforts to retrace and reimagine period tracking technology—or, mobile applications designed to support the documentation and quantification of menstrual cycle data. In their current form, these systems often encourage those who menstruate to extract intimate information about the body (e.g., consistency or color of menstrual flow, physical and emotional symptoms), while promising to predict fertility and offer insight into managing one's period. In doing so, these technologies subtly dictate the forms of knowledge and types of relationships menstruators are expected to establish with their bodies (i.e., transactional or instrumentalized). Through historical analysis and a series of participatory experiments, we offer a vision for menstrual sensemaking that expands on these forms of interaction and ways of knowing to emphasize multiplicity and dimensionality rather than models, predictability, or a user's relation to averages or norms.

Publisher

Association for Computing Machinery (ACM)

Subject

Human-Computer Interaction

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