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The Consensus Trap: Dissecting Subjectivity and the “Ground Truth” Illusion in Data Annotation
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The Application and Its Consequences for Non-Standard Knowledge Work
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As we may think
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Can “Conscious Data Contribution” Help Users to Exert “Data Leverage” Against Technology Companies?
Tech users currently have limited ability to act on concerns regarding the negative societal impacts of large tech companies. However, recent work suggests that users can exert leverage using their role in the generation of valuable data, for instance by withholding their data contributions to intelligent technologies. We propose and evaluate a new means to exert this type of leverage against tech companies: "conscious data contribution" (CDC).
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
Many powerful computing technologies rely on implicit and explicit data contributions from the public. In this paper, we synthesize emerging research that seeks to better understand and help people action this data leverage. Drawing on prior work in areas including machine learning, human-computer interaction, and fairness and accountability in computing, we present a framework for understanding data leverage that highlights new opportunities to change technology company behavior related to privacy, economic inequality, content moderation and other areas of societal concern.
The Politics of Open Infrastructures: Power, Governance, and Justice in Digital Knowledge Practices
This volume examines how openness is designed, governed, contested and lived in contemporary digital knowledge infrastructures. From open source software and internet standards, to citizen science platforms, public sector data systems and alternative computing practices, the book shows that infrastructures are never neutral technical backbones.
From novices to co-pilots: Fixing the limits on scientific knowledge production by accessing or building expertise
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Doing Data Science on the Shoulders of Giants: The Value of Open Source Software for the Data Science Community
Open source software is ubiquitous throughout data science, and enables the work of nearly every data scientist in some way or another. Open source projects, however, are disproportionately maintained by a small number of individuals, some of whom are institutionally supported, but many of whom do this maintenance on a purely volunteer basis. The health of the data science ecosystem depends on the support of open source projects, on an individual and institutional level.
A Polycentric Governance Lens on Data Infrastructures
Computer Supported Cooperative Work (CSCW) - Funding policies for data infrastructure promote open data sharing to drive positive social impact. However, concerns regarding the long-term management...
Local-first software: you own your data, in spite of the cloud
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The open authorial principle: supporting networks of authors in creating externalisable designs
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The Paradox of Open
Numerous organisations and initiatives have been launched with a belief in openness and free knowledge. Their proponents placed their bets on the combined power of networked information services and new governance models for the production and sharing of content and data. We – as members of this broad movement – were among those who believed it possible to leverage this combination of power and opportunity to build a more democratic society, unleashing the power of the internet to create universal access to knowledge and culture. For us, such openness meant not only freedom, but also presented a path to justice and equality.
Broadening Access to Data Science Education in High School and Higher Education through Open Source Tools, Infrastructure, and Training
Equitable data science education requires a multifaceted approach, involving high school and higher education, community involvement, and accessible tools. A renewed investment in public digital infrastructure is needed to support these efforts. Nonprofits play a crucial role in supporting these efforts, and increased representation in leadership can enhance their impact. By addressing these disparities, we can ensure a more inclusive future in data science.
Beyond Articles: Rethinking Diamond Open Access for a Data-Driven Research Future | CODATA Blog
What would it take for Diamond OA to evolve into a holistic, equitable, and data-rich scholarly ecosystem — one that meaningfully includes early-career researchers?
The operating system: should there be one?
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