Document Type

Article

Publication Date

2022

Abstract

Informed by critical data literacy efforts to promote social justice, this paper uses qualitative methods and data collected during two years of workplace ethnography to characterize the notion of critical novice data work. Specifically, we analyze everyday language used by novice data workers at DataWorks, an organization that trains and employs historically excluded populations to work with community data sets. We also characterize challenges faced by these workers in both cleaning and being critical of data during a project focused on police-community relations. Finally, we highlight novel approaches to visualizing data the workers developed during this project, derived from data cleaning and everyday experience. Findings and discussion highlight the generative power of everyday language and visualization for critical novice data work, as well as challenges and opportunities to foster critical data literacy with novice data workers in the workplace.

Comments

Previously published in:

Shapiro, B. R., Meng, A., Rothschild, A., Gilliam, S., Garrett, C., DiSalvo, C., & DiSalvo, B. (2022). “Bettering Data”: The Role of Everyday Language and Visualization in Critical Novice Data Work. Educational Technology & Society, 25 (4), 109- 125

https://www.j-ets.net/collection/published-issues/25_4

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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