{"title":"社区参与研究作为融入实践","authors":"J. Bay, K. Swacha","doi":"10.3998/mjcsloa.3239521.0026.108","DOIUrl":null,"url":null,"abstract":"This article presents an experiential model for communityengaged research that understands communities as living meshworks of embodied human beings, material circumstances, and affective environments. We first trace how community organizations and academics must increasingly respond to a push for hard data. Using an analysis of a national research study on hunger as an example, we then show how this “data imperative” can lead to collecting more and more measurable data on community members without addressing their humanbased concerns. The meshworks approach that we suggest emphasizes recognizing participants’ most immediate needs as articulated by participants. As meshworksinspired research has to be contingent and contextual within the meshworks of the community in which it takes place, we offer examples of what such research can look like in various community settings. Finally, we present a heuristic that community agencies and researchers can use to evaluate their own projects as meshworks while also gathering hard data.","PeriodicalId":93128,"journal":{"name":"Michigan journal of community service learning","volume":"71 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Community-Engaged Research as Enmeshed Practice\",\"authors\":\"J. Bay, K. Swacha\",\"doi\":\"10.3998/mjcsloa.3239521.0026.108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents an experiential model for communityengaged research that understands communities as living meshworks of embodied human beings, material circumstances, and affective environments. We first trace how community organizations and academics must increasingly respond to a push for hard data. Using an analysis of a national research study on hunger as an example, we then show how this “data imperative” can lead to collecting more and more measurable data on community members without addressing their humanbased concerns. The meshworks approach that we suggest emphasizes recognizing participants’ most immediate needs as articulated by participants. As meshworksinspired research has to be contingent and contextual within the meshworks of the community in which it takes place, we offer examples of what such research can look like in various community settings. Finally, we present a heuristic that community agencies and researchers can use to evaluate their own projects as meshworks while also gathering hard data.\",\"PeriodicalId\":93128,\"journal\":{\"name\":\"Michigan journal of community service learning\",\"volume\":\"71 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Michigan journal of community service learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3998/mjcsloa.3239521.0026.108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Michigan journal of community service learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3998/mjcsloa.3239521.0026.108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This article presents an experiential model for communityengaged research that understands communities as living meshworks of embodied human beings, material circumstances, and affective environments. We first trace how community organizations and academics must increasingly respond to a push for hard data. Using an analysis of a national research study on hunger as an example, we then show how this “data imperative” can lead to collecting more and more measurable data on community members without addressing their humanbased concerns. The meshworks approach that we suggest emphasizes recognizing participants’ most immediate needs as articulated by participants. As meshworksinspired research has to be contingent and contextual within the meshworks of the community in which it takes place, we offer examples of what such research can look like in various community settings. Finally, we present a heuristic that community agencies and researchers can use to evaluate their own projects as meshworks while also gathering hard data.