Christine Debora Irene, Thinyane Mamello
United Nations University Institute in Macau, Casa Silva Mendes, Estrada do Engenheiro Trigo No. 4, Macau SAR, China.
Patterns (N Y). 2021 Mar 23;2(4):100224. doi: 10.1016/j.patter.2021.100224. eCollection 2021 Apr 9.
Citizen science has been motivated by several perspectives, including increased efficiency in data collection and distributed analysis, democratizing knowledge production, making science more responsive to community needs, and improving the representation of marginalized populations in public data. Despite the potential of citizen science to achieve social justice agendas through a data-intensive and data-driven participatory scientific enquiry, scholarship in critical data studies offers several problematizations of data-based practices, highlighting risks of exclusion and inequality. To understand the extent to which citizen science supports and challenges forms of injustice, this study used a "data justice" analytical framework to critically explore the assemblages of citizen science. We examined four citizen science cases with different levels of citizen engagement, intended outcomes, and data systems. The analysis suggests instances of injustice occurring throughout the data processes of the citizen science cases across the dimensions of procedural, instrumental, rights-based, structural, and distributive data justice.
公民科学受到多种观点的推动，包括提高数据收集和分布式分析的效率、使知识生产民主化、让科学更能响应社区需求以及改善公共数据中边缘化人群的代表性。尽管公民科学有潜力通过数据密集型和数据驱动的参与式科学探究来实现社会正义议程，但批判性数据研究领域的学术成果对基于数据的实践提出了若干质疑，突出了排斥和不平等的风险。为了了解公民科学在多大程度上支持和挑战不公正形式，本研究使用了一个“数据正义”分析框架来批判性地探索公民科学的组合。我们考察了四个公民科学案例，这些案例在公民参与程度、预期成果和数据系统方面各不相同。分析表明，在公民科学案例的数据过程中，在程序、工具、基于权利、结构和分配性数据正义等维度上都存在不公正的情况。
