UPDATE: The deadline for this Call for Proposals closed on April 1, 2023. If you are interested in learning more about this project or have specific questions, please contact us at [email protected].
The Do No Harm Project is a series of reports that provide guidance for researchers and analysts who want to approach their work through a lens of diversity, equity, and inclusion. Rather than prescribing what to do or not do, the studies encourage thoughtfulness in how analysts work with and present their data. The September 2022 report, Do No Harm Guide: Additional Perspectives on Data Equity, consists of five contributed essays from data experts and practitioners whose voices have been traditionally underrepresented in the field.
We are seeking proposals for 3- to 4-page essays (about 2,000 words) on how you take, or how you would like others to take, a more equitable and inclusive approach to data work. Authors invited to turn their proposal into an essay for this Do No Harm Guide will receive technical and editorial support from Urban Institute staff, have their essay published on urban.org, and receive an honorarium of $500 USD.
Proposals will be reviewed on a rolling basis, with a final deadline of April 1, 2023. Review criteria will include the proposal’s originality, feasibility, and relevance to the Do No Harm Project. For this project, we are focusing on data visualization experiences within the United States; if you have experiences from other areas, please see our other call for papers, which focuses on international perspectives.
Essays We’re Seeking
We are looking for analysis of current data practices—from the data collection, data analysis, and data communication stages—that can help other analysts be more inclusive and equitable in their data work.
Analyses may consist of case studies, critiques about existing data practices or methods, or specific data visualization or data communication approaches. The goal of the essays is to inform other data analysts and communicators on how to take an equitable approach to their data work. The best essays will clearly diagnose a problem, explore the reasons the problem exists and the systems that maintain it, and offer recommendations to address the problem.
This opportunity is open to all researchers and analysts with an interest in equity, inclusivity, and diversity. Joint proposals are welcome, though the honorarium is provided per essay.
Process for Selected Proposals
Authors should submit an abstract of about 200 words using this Qualtrics form. Authors of selected proposals will develop their ideas into a short essay of 3 to 4 pages, or approximately 2,000 words, including any supporting figures or tables. We plan to select about 8 to 12 essays for inclusion in the final report.
Authors invited to develop their proposals into essays will receive the support of Urban staff, including feedback on substance and style, as they refine their idea, conduct the analysis, and write their results. All products will go through Urban’s quality assurance and editorial processes. Authors will own their work while providing a license to Urban to publish and disseminate it, and they will be free to further develop their analyses for publication in other outlets (such as academic journals).
Proposal Process
The proposal form asks applicants to respond to the following questions:
- Which data or data-related area do you propose to analyze?
- Which area of the data workflow do you intend to focus on?
- Data collection
- Data analysis
- Data communication (e.g., data visualization)
- All three
- Which group or groups traditionally underrepresented in data work does this issue most greatly affect?
- Are you a member of this underrepresented group, or do you have other lived experiences that would make you a successful author on the proposed topic?
- In one sentence, what is the key takeaway of your proposal?
- Please summarize how you will support that key takeaway in no more than 250 words.
- Why are you the right person to write this analysis?
Feel free to contact us with any questions at [email protected].
