What's Missing from Data Modernization? A Focus on Structural Racism
Public health data modernization efforts frequently overlook the far-reaching effects of structural racism across the data life cycle. Modernizing data requires creating data ecosystems grounded in six principles: dismantling structural racism and building community power explicitly; centering justi...
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| Format: | Book |
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| Published: |
Mary Ann Liebert,
2023-10-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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| Summary: | Public health data modernization efforts frequently overlook the far-reaching effects of structural racism across the data life cycle. Modernizing data requires creating data ecosystems grounded in six principles: dismantling structural racism and building community power explicitly; centering justice in all stages of data collection and analysis; ensuring communities can govern their data; driving positive population-level change; engaging nonprofit organizations; and obtaining commitments from governments to make changes in policy and practice. As government agencies spearhead and finance data modernization initiatives, it is imperative that they address structural racism head-on and integrate these principles into all aspects of their work. |
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| Item Description: | 10.1089/HEQ.2023.0086 2473-1242 |