Explore, engage, empower: methodological insights into a transformative mixed methods study tackling the COVID-19 lockdown

Claudia Rebeca Binder Signer, Garance Clément, Laurie Daffe, Livia Bianca Fritz, Daniel Gatica-Perez, Vincent Kaufmann, Anna Pagani, Melissa Pang, Ulrike Vilsmaier
2022
Journal paper

Abstract

Action-oriented, transformative, and transdisciplinary approaches are increasingly heralded as promising tools that enable researchers not only to produce new knowledge about a situation, but also to actively engage in tackling it; however, such approaches raise critical questions about the methodological implications and conflicts involved in pursuing multiple objectives concurrently. This article seeks to advance this debate by examining the methodological implications of pursuing both knowledge production-oriented (epistemic) and action-oriented (transformative) objectives in urgent and uncertain situations. It asks how far a transformative mixed methods research design can leverage the potential of research to achieve multiple objectives in times of crisis. This methodological inquiry is based on a transformative mixed methods study on housing conditions and well-being which was initiated during the first COVID-19 lockdown in Switzerland. The study was composed of a country-wide survey, mobile crowdsourcing, interviews and Citizen Think Tanks. The results of this methodological reflection illustrate how this research design made it possible to (i) explore the effects of the crisis on domestic living spaces, (ii) engage with the crisis in a joint research space, and (iii) stimulate empowerment through reflection and mutual learning. These insights suggest the multidimensional orientation of the transformative mixed methods approach is appropriate for acting upon urgent crises. However, it challenges core methodological values and research constellations including (i) tackling unequal engagement opportunities, (ii) navigating social and epistemic control, and (iii) paying attention to situatedness and positionality. The article concludes that, in anticipation of future crises, favorable conditions for multi-targeted, collaborative research need to be fostered, both on the institutional and on personal levels. These conditions should enable fast and adequate team formation, as well as reflection and negotiation of positionalities, and divergent interests and objectives, of both scientists and citizens.

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Claudia Rebeca Binder Signer, Garance Clément, Laurie Daffe, Livia Bianca Fritz, Daniel Gatica-Perez, Vincent Kaufmann, Anna Pagani, Melissa Pang, Ulrike Vilsmaier
2022
Journal paper

Abstract

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https://infoscience.epfl.ch/record/294068?ln=en

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Three essays on the role of proximity in science and innovation

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EPFL2015

Enhancing Social Media Platforms for Educational and Humanitarian Knowledge Sharing

Andrii Vozniuk

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EPFL2017

Concerns over the ever-increasing production, availability and use of multilayered individual data in social research, business and the everyday life calls for the development of ethical and legal guidelines. In parallel to civic and governmental initiatives, Critical Data Studies offers a transdisciplinary academic platform to define a common ethical framework for computational research. Essays recently published under this label argue for lines of conduct guided by principles such as fairness and justice. Cultural and evolutionary anthropology, as well as political psychology show, however, those principles are mostly common to Northern liberal cultures. For example, Moral Foundation Theory identifies five cross-cultural grounds to ethical reasoning—Fairness, Care, Authority, In-group and Purity—the first two being associated with progressive views, and the three others with traditionalist views. In the current development of Critical Data Studies, the framing of research ethics by fairness and justice therefore risks to maintain, if not increase, the hegemony of Northern researchers on scientific productivity in Big Data research. In this poster, I present a novel framing of Big Data ethics, one that considers the cross-cultural diversity of human morality. My objective is to lay out a shared ground to an urging global approach to knowledge production. First, I review existing ethical framework of Big Data research and classify each proposal according to the Moral Foundation Theory. Second, I identify commonalities and gaps of proposed framework and articulate possible extension of each framework using the missing moral foundations as guiding principles. Finally, I propose a synthetic framework of Big Data ethics. The poster highlights the unbalance of ethical considerations in Big Data research, and in scientific production in general. The proposed framework points at ethical stances that could become major concerns in future research using Big Data for social research: Political or economic definition of scientific objectives, applications and limitations (authority); Exclusion of individuals, groups and communities in the production, publication and application of research findings (in-group); Constrains on inter- and transdisciplinary collaborations, research topics, methods of analysis, epistemic positioning and ontological grounds (purity).

2018