Participatory Field Experiments and Causal Inference for Monitoring and Advancing Social Justice in HCI

Causal research is valuable for identifying social injustices, determining their causes, and intervening to expand human dignity. Yet quantitative, causal methods have historically been associated with substantial risks to social justice. This paper outlines a possible direction for “participatory field experiments," causal, social justice HCI methods derived from participatory and emancipatory action research.

Publication Details

Journal
Open Science Framework
Published
2025-01-01
DOI
https://doi.org/10.17605/osf.io/pd76b
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
0.00
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article

Participatory Field Experiments and Causal Inference for Monitoring and Advancing Social Justice in HCI

Open Science Framework
Innovative Human-Technology Interaction
article

Participatory Field Experiments and Causal Inference for Monitoring and Advancing Social Justice in HCI

article en

Abstract

Causal research is valuable for identifying social injustices, determining their causes, and intervening to expand human dignity. Yet quantitative, causal methods have historically been associated with substantial risks to social justice. This paper outlines a possible direction for “participatory field experiments," causal, social justice HCI methods derived from participatory and emancipatory action research.

Open Science Framework
Reduced inequalities
Openalex Percentile: Top 56%
Innovative Human-Technology Interaction
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Participatory Field Experiments and Causal Inference for Monitoring and Advancing Social Justice in HCI · Open Science Framework (2025) | TGRS Research Map | TGRS