Work

The CODE^SHIFT model: a data justice framework for collective impact and social transformation

Year: 2023

Type: article

Abstract: In this article, we present an alternative framework that resists hegemonic social sciences within data-driven communication theorizing through a culture-centered approach (CCA). Building on the CCA in co-creating voice infrastructures at the margins, we argue that data justice requires transforming interpretive data framings, disrupting the hegemonic registers of knowledge production constituted around data, and working with/through data to challenge the structures of capitalism and colonialism that circulate the practices of exploitation and extraction. We build upon community-engaged projects emergent from the CCA in/with/from the Global South to propose the CODE^SHIFT Model, grounded in principles of equity-mindedness, collective impact, purposiveness, and systemic change. It highlights what data justice looks like in various stages of community-led transformation: identifying pressing social problems; bridging cross-sector coalitions and partnerships; organizing for collective impact activities; and sustaining capacity building. We reframe data as pluriversal, embodied, sacred, sovereign, disruptive, solidarity, and impossibility.

Source: Human Communication Research

DOI: 10.1093/hcr/hqad050

Authors: Srividya Ramasubramanian, Mohan J Dutta

Institutions: Syracuse University, Massey University

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Peace, justice, and strong institutions

Open Access status: hybrid

Estimated APC paid: $3,878