Robert W. Ressler, Michelle Weiner, Dolores Acevedo-Garcia
{"title":"In Conversation with Equity: Qualitatively Engaging Quantitative Data for Equitable Social Impact","authors":"Robert W. Ressler, Michelle Weiner, Dolores Acevedo-Garcia","doi":"10.1080/10999922.2023.2264413","DOIUrl":null,"url":null,"abstract":"AbstractMaking meaningful progress towards achieving racial equity in public serving institutions requires making equity-informed decisions, which itself requires the use of equity-oriented data. Public and nonprofit organizations, however, are at varying degrees of readiness to use this data and to make equity-focused decisions. We draw on qualitative research to examine how children’s hospitals use equity-focused neighborhood data to understand racial/ethnic inequities in the populations they serve and eventually to make decisions that can help correct these inequities. The interactions between data producers and users involve not only technical exchanges, but also the adoption of shared analytic frameworks that center equity, as well as “nervous” conversations. Our analysis indicates that qualitative interrogations of the use of quantitative data within organizations may help to overcome knowledge, organization, and equity readiness barriers to equitable outcomes. Using equity-focused data for data-driven decision-making is relational, so qualitative research methods can facilitate the reflexivity and critical mindsets needed to change organizational practices to improve racial equity. Employing qualitative methods can help data producers make their construction and dissemination of data more rigorous. Facilitating equity conversations can also help improve relationships with data users, which is necessary for data collaborations to promote racial equity.Keywords: Racial equitydataorganizationsqualitative methods AcknowledgmentsThank you to Lindsay Rosenfeld and Jessica Kramer for your helpful input in previous drafts as well as to the many users of the COI, including those that contributed to this research.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The COI 2.0 is a composite index of neighborhood opportunity for children measured at the census tract level. It has been developed by the diversitydatakids.org project at Heller School for Social Policy and Management, Brandeis University, of which we are a part. Complete index data, documentation, and a COI interactive map are available at the project website, diversitydatakids.org.2 We use pseudonyms and gender-neutral language for all participants to preserve anonymity.Additional informationFundingThe work was supported by the Robert Wood Johnson Foundation [grant 71192] and the W.K. Kellogg Foundation [grant P3036220]. The sponsors played no role in study design, analysis, interpretation of data, writing of the manuscript, or submission for publication. There was no additional external funding received for this study.","PeriodicalId":51805,"journal":{"name":"Public Integrity","volume":"46 1","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Integrity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10999922.2023.2264413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC ADMINISTRATION","Score":null,"Total":0}
引用次数: 0
Abstract
AbstractMaking meaningful progress towards achieving racial equity in public serving institutions requires making equity-informed decisions, which itself requires the use of equity-oriented data. Public and nonprofit organizations, however, are at varying degrees of readiness to use this data and to make equity-focused decisions. We draw on qualitative research to examine how children’s hospitals use equity-focused neighborhood data to understand racial/ethnic inequities in the populations they serve and eventually to make decisions that can help correct these inequities. The interactions between data producers and users involve not only technical exchanges, but also the adoption of shared analytic frameworks that center equity, as well as “nervous” conversations. Our analysis indicates that qualitative interrogations of the use of quantitative data within organizations may help to overcome knowledge, organization, and equity readiness barriers to equitable outcomes. Using equity-focused data for data-driven decision-making is relational, so qualitative research methods can facilitate the reflexivity and critical mindsets needed to change organizational practices to improve racial equity. Employing qualitative methods can help data producers make their construction and dissemination of data more rigorous. Facilitating equity conversations can also help improve relationships with data users, which is necessary for data collaborations to promote racial equity.Keywords: Racial equitydataorganizationsqualitative methods AcknowledgmentsThank you to Lindsay Rosenfeld and Jessica Kramer for your helpful input in previous drafts as well as to the many users of the COI, including those that contributed to this research.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The COI 2.0 is a composite index of neighborhood opportunity for children measured at the census tract level. It has been developed by the diversitydatakids.org project at Heller School for Social Policy and Management, Brandeis University, of which we are a part. Complete index data, documentation, and a COI interactive map are available at the project website, diversitydatakids.org.2 We use pseudonyms and gender-neutral language for all participants to preserve anonymity.Additional informationFundingThe work was supported by the Robert Wood Johnson Foundation [grant 71192] and the W.K. Kellogg Foundation [grant P3036220]. The sponsors played no role in study design, analysis, interpretation of data, writing of the manuscript, or submission for publication. There was no additional external funding received for this study.