{"status":"OK","data":{"id":59975,"identifier":"DVN/GD6WCP","persistentUrl":"https://doi.org/10.7910/DVN/GD6WCP","protocol":"doi","authority":"10.7910","separator":"/","publisher":"Harvard Dataverse","publicationDate":"2011-05-09","storageIdentifier":"s3://10.7910/DVN/GD6WCP","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":988,"datasetType":"dataset","locks":[],"latestVersion":{"id":61202,"datasetId":59975,"datasetPersistentId":"doi:10.7910/DVN/GD6WCP","datasetType":"dataset","storageIdentifier":"s3://10.7910/DVN/GD6WCP","versionNumber":1,"internalVersionNumber":1,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionNote":"Initial version","deaccessionLink":"","lastUpdateTime":"2010-05-03T18:16:55Z","releaseTime":"2011-05-09T00:00:00Z","createTime":"2010-05-03T17:55:16Z","alternativePersistentId":"hdl:1902.1/14657","publicationDate":"2011-05-09","citationDate":"2011-05-09","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":988,"license":{"name":"CC0 1.0","uri":"http://creativecommons.org/publicdomain/zero/1.0","iconUri":"https://licensebuttons.net/p/zero/1.0/88x31.png","rightsIdentifier":"CC0-1.0","rightsIdentifierScheme":"SPDX","schemeUri":"https://spdx.org/licenses/","languageCode":"en"},"fileAccessRequest":false,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Reconsidering Deinstitutionalization: The Relevance of Space and the Poverty Threshold for the Presence of Organizational Resources"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Carly Knight"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Harvard University"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Jessica Simes"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Harvard University"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactEmail":{"typeName":"datasetContactEmail","multiple":false,"typeClass":"primitive","value":"N/A"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"In 2006, Mario Luis Small and Monica McDermott published, \"The Presence of Organizational Resources in Poor Urban Neighborhoods: An Analysis of Average and Contextual Effects\" in Social Forces. Cited by several proceeding works as a challenge to a widely supported theory of inner city ghetto deinstitutionalization presented by William Julius Wilson and others, the authors quantitatively tested the proposition that poverty inhibits neighborhood organizational resources. Re-examining their findings using disaggregated data and adjusting for non-linearity, we find evidence in support of both their findings as well as Wilson's original hypotheses. While poverty is in fact positively associated with organizational density for low-poverty neighborhoods, this effect reverses and becomes negative for high-poverty neighborhoods. Moreover, the effect of poverty within poor, inner city urban neighborhoods is universally negative. This empirical finding emphasizes a wider need within urban sociological research to identify the levels at which key independent variables of interest exert their effect. Indeed, rather than engage in wholesale refutation or vindication of competing theories, our methods allow us to hypothesize and evaluate where particular theories should be expected to hold. Finally, we argue that neighborhood change is a key aspect to understanding available resources for the urban poor."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2010-05-03"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Small, Mario and Monica McDermott. \"The Presence of Organizational Resources in Poor Urban Neighborhoods: An Analysis of Average and Contextual Effects.\" Social Forces. Volume 84, Number 3, March 2006, pp. 1697-1724."}}]},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2010-05-03"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2000"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2000"}}]}]},"geospatial":{"displayName":"Geospatial Metadata","name":"geospatial","fields":[{"typeName":"geographicCoverage","multiple":true,"typeClass":"compound","value":[{"country":{"typeName":"country","multiple":false,"typeClass":"controlledVocabulary","value":"United States"}}]},{"typeName":"geographicUnit","multiple":true,"typeClass":"primitive","value":["Census Tract, Zip Code and MSA/PMSA"]}]}},"files":[{"description":"Complete dataset for census tract level variables","label":"analysisfile_ctract_historical.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549350,"persistentId":"doi:10.7910/DVN/GD6WCP/07NLOY","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/07NLOY","filename":"analysisfile_ctract_historical.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":38803685,"description":"Complete dataset for census tract level variables","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56622","rootDataFileId":-1,"md5":"08b7fd7e47a3d76f0fedaa5a83ffa778","checksum":{"type":"MD5","value":"08b7fd7e47a3d76f0fedaa5a83ffa778"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Census tract with poverty interaction variable","label":"analysisfile_ctract_povinteract3.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549351,"persistentId":"doi:10.7910/DVN/GD6WCP/HVTIA1","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/HVTIA1","filename":"analysisfile_ctract_povinteract3.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":53639079,"description":"Census tract with poverty interaction variable","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56623","rootDataFileId":-1,"md5":"4e100b40043735fb4698c58187aaef7d","checksum":{"type":"MD5","value":"4e100b40043735fb4698c58187aaef7d"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Complete Data for MSA/PMSA level variables","label":"analysisfile_msapmsa_historical.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549352,"persistentId":"doi:10.7910/DVN/GD6WCP/ZTWZ2N","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/ZTWZ2N","filename":"analysisfile_msapmsa_historical.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":3078,"description":"Complete Data for MSA/PMSA level variables","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56624","rootDataFileId":-1,"md5":"42731983fcd933e129e4bd2a856c39b6","checksum":{"type":"MD5","value":"42731983fcd933e129e4bd2a856c39b6"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"HLM model for census tract analysis","label":"Ctract_Ba2006_050210.mdm","restricted":false,"version":1,"datasetVersionId":61202,"categories":["HLM MDM"],"dataFile":{"id":1549356,"persistentId":"doi:10.7910/DVN/GD6WCP/BXWZ8Q","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/BXWZ8Q","filename":"Ctract_Ba2006_050210.mdm","contentType":"application/octet-stream","friendlyType":"Unknown","filesize":10419669,"description":"HLM model for census tract analysis","categories":["HLM MDM"],"storageIdentifier":"s3://dvn-cloud:56631","rootDataFileId":-1,"md5":"f2bcf86c61da049541b71f0395418759","checksum":{"type":"MD5","value":"f2bcf86c61da049541b71f0395418759"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Merges exported GIS Datasets with Census Tract ","label":"DataAdmin1_MSAPMSA_42710.sas","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data Management"],"dataFile":{"id":1549368,"persistentId":"doi:10.7910/DVN/GD6WCP/0YUMFK","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/0YUMFK","filename":"DataAdmin1_MSAPMSA_42710.sas","contentType":"text/x-sas-syntax; charset=US-ASCII","friendlyType":"SAS Syntax","filesize":8662,"description":"Merges exported GIS Datasets with Census Tract ","categories":["Data Management"],"storageIdentifier":"s3://dvn-cloud:56639","rootDataFileId":-1,"md5":"e29164c897518f5dee19b5655c5c93df","checksum":{"type":"MD5","value":"e29164c897518f5dee19b5655c5c93df"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Calculates the poverty interactions and generates descriptive statistics","label":"DataAnalysis_CensusLevel_42710.R","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data Management"],"dataFile":{"id":1549369,"persistentId":"doi:10.7910/DVN/GD6WCP/L2UIZC","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/L2UIZC","filename":"DataAnalysis_CensusLevel_42710.R","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":12666,"description":"Calculates the poverty interactions and generates descriptive statistics","categories":["Data Management"],"storageIdentifier":"s3://dvn-cloud:56645","rootDataFileId":-1,"md5":"c8341066c42b45fdbcbfaa786fd675ac","checksum":{"type":"MD5","value":"c8341066c42b45fdbcbfaa786fd675ac"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"File Manifest for all Files","label":"File Manifest.docx","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Documentation"],"dataFile":{"id":1549370,"persistentId":"doi:10.7910/DVN/GD6WCP/CC4FZ8","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/CC4FZ8","filename":"File Manifest.docx","contentType":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","friendlyType":"MS Word","filesize":13193,"description":"File Manifest for all Files","categories":["Documentation"],"storageIdentifier":"s3://dvn-cloud:56646","rootDataFileId":-1,"md5":"4608fc8b2ebcb6830bf6672ba4595429","checksum":{"type":"MD5","value":"4608fc8b2ebcb6830bf6672ba4595429"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Data for calculating poverty coefficients","label":"povcoefs.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549353,"persistentId":"doi:10.7910/DVN/GD6WCP/KEPDNC","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/KEPDNC","filename":"povcoefs.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":1252,"description":"Data for calculating poverty coefficients","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56625","rootDataFileId":-1,"md5":"8c1af83141539e7716af498ac2f786b9","checksum":{"type":"MD5","value":"8c1af83141539e7716af498ac2f786b9"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Data to calculate the poverty thresholds","label":"povertylevel.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549354,"persistentId":"doi:10.7910/DVN/GD6WCP/OGWQTA","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/OGWQTA","filename":"povertylevel.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":87,"description":"Data to calculate the poverty thresholds","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56628","rootDataFileId":-1,"md5":"f6662d5bd8313902fd50a73129f48fdf","checksum":{"type":"MD5","value":"f6662d5bd8313902fd50a73129f48fdf"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"Data for calculating urbanicity levels","label":"urbanicity.csv","restricted":false,"version":1,"datasetVersionId":61202,"categories":["Data"],"dataFile":{"id":1549355,"persistentId":"doi:10.7910/DVN/GD6WCP/N6UH89","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/N6UH89","filename":"urbanicity.csv","contentType":"text/plain; charset=US-ASCII","friendlyType":"Plain Text","filesize":75,"description":"Data for calculating urbanicity levels","categories":["Data"],"storageIdentifier":"s3://dvn-cloud:56629","rootDataFileId":-1,"md5":"aeba51fa79c3f5d0b8c6ec6bb0b5050a","checksum":{"type":"MD5","value":"aeba51fa79c3f5d0b8c6ec6bb0b5050a"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"HLM mdm for zip code level analysis with Business Analyst Data","label":"Zip_Ba2006_050210_2.mdm","restricted":false,"version":1,"datasetVersionId":61202,"categories":["HLM MDM"],"dataFile":{"id":1549357,"persistentId":"doi:10.7910/DVN/GD6WCP/MKKRKQ","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/MKKRKQ","filename":"Zip_Ba2006_050210_2.mdm","contentType":"application/octet-stream","friendlyType":"Unknown","filesize":1691392,"description":"HLM mdm for zip code level analysis with Business Analyst Data","categories":["HLM MDM"],"storageIdentifier":"s3://dvn-cloud:56634","rootDataFileId":-1,"md5":"7fad3f837aa96ab7e1ab03533ccee42a","checksum":{"type":"MD5","value":"7fad3f837aa96ab7e1ab03533ccee42a"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}},{"description":"HLM mdm for analysis of original zip-code data from Small and McDermott (2006)","label":"Zip_Small2006_50210.mdm","restricted":false,"version":1,"datasetVersionId":61202,"categories":["HLM MDM"],"dataFile":{"id":1549361,"persistentId":"doi:10.7910/DVN/GD6WCP/KLHKEF","pidURL":"https://doi.org/10.7910/DVN/GD6WCP/KLHKEF","filename":"Zip_Small2006_50210.mdm","contentType":"application/octet-stream","friendlyType":"Unknown","filesize":2935374,"description":"HLM mdm for analysis of original zip-code data from Small and McDermott (2006)","categories":["HLM MDM"],"storageIdentifier":"s3://dvn-cloud:56636","rootDataFileId":-1,"md5":"6f87760c6cd7f597981ef27900d96de9","checksum":{"type":"MD5","value":"6f87760c6cd7f597981ef27900d96de9"},"tabularData":false,"creationDate":"2010-05-03","publicationDate":"2011-05-08","lastUpdateTime":"2010-05-03T18:16:55Z","fileAccessRequest":false}}]}}}