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Scientific research is not value-neutral but builds on the stated and unstated values of those leading the research, influencing the choice of study topics; decisions about methods, judgments, or inferences with data; and considerations of the consequences of errors. In some fields, researchers create a positionality statement to disclose bias as a way to manage or neutralize the influence of values. Positionality refers to the way in which an individual’s worldview, and thus perceptions and research activities, is shaped by the frameworks, social identities, lived experiences, and sociopolitical context within which they live. Thinking about positionality is a valuable, yet missing, element for practitioners of participatory sciences. In this essay, we suggest that those leading participatory science projects explore their positionality, irrespective of whether or not they choose to disclose it, in order to manage values for several goals: research integrity, ethical data practices, and equity and inclusion. By reviewing and synthesizing literature, we created a tool to help leaders of participatory science projects think reflectively (for awareness of their identities and characteristics) and reflexively (from an external position for critical observation of themselves) to recognize their influence on project design and implementation. We view examining positionality as a precursor to anticipating and taking actions to minimize epistemic injustices and ultimately enhance the unique capacity of each project to advance equity, inclusion, and scientific productivity.
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Getting Ourselves Together: Data-centered participatory design research & epistemic burden
Data-centered participatory design research projects—wherein researchers collaborate with community members for the purpose of gathering, generating, or communicating data about the community or their causes—can place epistemic burdens on minoritized or racialized groups, even in projects focused on social justice outcomes. Analysis of epistemic burden encourages researchers to rethink the purpose and value of data in community organizing and activism more generally. This paper describes three varieties of epistemic burden drawn from two case studies based on the authors’ previous work with anti-police brutality community organizations. The authors conclude with a discussion of ways to alleviate and avoid these issues through a series of questions about participatory research design. Ultimately, we call for a reorientation of knowledge production away from putative design solutions to community problems and toward a more robust interrogation of the power dynamics of research itself.
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- Award ID(s):
- 1901367
- PAR ID:
- 10284251
- Date Published:
- Journal Name:
- CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1 - 11
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3411764.3445103
