{"status":"OK","data":{"id":47081,"identifier":"DVN/KERPJC","persistentUrl":"https://doi.org/10.7910/DVN/KERPJC","protocol":"doi","authority":"10.7910","separator":"/","publisher":"Harvard Dataverse","publicationDate":"2011-07-19","storageIdentifier":"s3://1902.1/16313","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":996,"datasetType":"dataset","locks":[],"latestVersion":{"id":43265,"datasetId":47081,"datasetPersistentId":"doi:10.7910/DVN/KERPJC","datasetType":"dataset","storageIdentifier":"s3://1902.1/16313","versionNumber":5,"internalVersionNumber":1,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionNote":"","deaccessionLink":"","distributionDate":"2008","productionDate":"2008","UNF":"UNF:5:KSpUdTV8nPBD5KgsY9gdqA==","lastUpdateTime":"2011-07-19T18:22:45Z","releaseTime":"2011-07-19T00:00:00Z","createTime":"2011-07-19T18:22:45Z","alternativePersistentId":"hdl:1902.1/16313","publicationDate":"2011-07-19","citationDate":"2011-07-19","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":996,"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":"Bridging Partisan Division over Anti-Terrorism Policies: The Role of Threat Perceptions"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Neil Malhotra"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Stanford University. Department of Political Science."}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Elizabeth Popp"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"University of Illinois at Urbana-Champaign. Department of Political Science."}}]},{"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":"This study examines how changes in perceptions of threat affect individuals’ policy views, as well as the political implications of this relationship. A survey experiment was administered to a representative sample of the U.S. population in which individuals’ perceived likelihood of a future terrorist attack on American soil was manipulated. The purpose of the survey is to address two hypotheses which state that a higher perceived threat from a terrorist attack will make individuals more supportive of public policies designed to combat terrorism and the effect of threat\ninformation on support of public policies designed to combat terrorism will be stronger among Democrats who believe an attack is likely.  The respondents were picked for the study through Random Digit Dialing administered by Knowledge Networks and sent a questionnaire over the Internet.  Variables treated in this study fall into two general groups: demographics and attitudes towards anti-terrorism polices. Demographic variables include race, age, education, income, and geographic region. The anti-terrorism policy variables revolve around four broad questions that deal with wire-taps, libraries reporting to the federal government, airline restrictions, and U.S. military attacks against terrorism."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2011"}}]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"ideologies"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"law enforcement/first responder"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"terrorism"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"perceptions"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Malhotra, N., & Popp, E. (2010). Bridging partisan divisions over antiterrorism policies: The role of threat perceptions. Political Research Quarterly (DOI: 10.1177/1065912910385251)."}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"Subject: Study Level Error Note, Notes: Limitations include nonresponse and noncoverage bias but these limitations were addressed by applying post-stratification adjustments.;"},{"typeName":"producer","multiple":true,"typeClass":"compound","value":[{"producerName":{"typeName":"producerName","multiple":false,"typeClass":"primitive","value":"Knowledge Networks"},"producerAbbreviation":{"typeName":"producerAbbreviation","multiple":false,"typeClass":"primitive","value":"KN"},"producerURL":{"typeName":"producerURL","multiple":false,"typeClass":"primitive","value":"http://www.knowledgenetworks.com/index.html"},"producerLogoURL":{"typeName":"producerLogoURL","multiple":false,"typeClass":"primitive","value":"http://www.knowledgenetworks.com/images/knlogo2010.gif"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2008"},{"typeName":"distributor","multiple":true,"typeClass":"compound","value":[{"distributorName":{"typeName":"distributorName","multiple":false,"typeClass":"primitive","value":"Time-Sharing Experiments for the Social Sciences"},"distributorAbbreviation":{"typeName":"distributorAbbreviation","multiple":false,"typeClass":"primitive","value":"TESS"},"distributorURL":{"typeName":"distributorURL","multiple":false,"typeClass":"primitive","value":"http://www.tessexperiments.org/index.html"},"distributorLogoURL":{"typeName":"distributorLogoURL","multiple":false,"typeClass":"primitive","value":"http://www.tessexperiments.org/TESSLogo.jpg"}}]},{"typeName":"distributionDate","multiple":false,"typeClass":"primitive","value":"2008"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2011-07-19"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2008-03-21"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2008-03-31"}}]},{"typeName":"dateOfCollection","multiple":true,"typeClass":"compound","value":[{"dateOfCollectionStart":{"typeName":"dateOfCollectionStart","multiple":false,"typeClass":"primitive","value":"2008-03-21"},"dateOfCollectionEnd":{"typeName":"dateOfCollectionEnd","multiple":false,"typeClass":"primitive","value":"2008-03-31"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["survey data"]}]},"geospatial":{"displayName":"Geospatial Metadata","name":"geospatial","fields":[{"typeName":"geographicCoverage","multiple":true,"typeClass":"compound","value":[{"otherGeographicCoverage":{"typeName":"otherGeographicCoverage","multiple":false,"typeClass":"primitive","value":"United States (Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming)"}},{"otherGeographicCoverage":{"typeName":"otherGeographicCoverage","multiple":false,"typeClass":"primitive","value":"North America"}}]},{"typeName":"geographicUnit","multiple":true,"typeClass":"primitive","value":["State"]}]},"socialscience":{"displayName":"Social Science and Humanities Metadata","name":"socialscience","fields":[{"typeName":"unitOfAnalysis","multiple":true,"typeClass":"primitive","value":["Individual"]},{"typeName":"universe","multiple":true,"typeClass":"primitive","value":["The population of interest is American adults."]},{"typeName":"samplingProcedure","multiple":false,"typeClass":"primitive","value":"A questionnaire was created to test the two main hypothesis and began with a brief statement about findings from an actual survey of arms control experts conducted by the Senate Foreign Relations Committee. Respondents were asked to read the following passage, in which the information was manipulated regarding the percentage chance of the terrorist attack. The respondents were picked through Random Digit Dialing administered by Knowledge Networks and sent a questionnaire over the Internet. Two strata are used in the RDD sampling process based on 2000 Census Decennial Census with the first stratum having a higher concentration of Black and Hispanic households and the second stratum having a lower concentration relative to the national estimates. The survey sample was picked according to the researchers' screening criteria and respondents filled out the questionnaire and return it by email."},{"typeName":"collectionMode","multiple":true,"typeClass":"primitive","value":["e-mail interview"]},{"typeName":"weighting","multiple":false,"typeClass":"primitive","value":"Seven post-stratification weights are incorporated into this study. The first is half-sampling of telephone numbers for which no address could be found. The second is RDD sampling rates proportional to the number of phone lines in the household. The third is minor oversampling of Chicago and Los Angeles due to early pilot surveys in these two cities. The fourth is short-term double-sampling of the four largest states (CA, NY, FL, and TX) and central region states. The fifth is under-sampling of households not covered by MSN TV. The sixth is oversampling of minority households (Black and Hispanic). Finally, the seventh weight is the selection of one adult per household. In order to calculate final weights, the researchers derived weighted sample distributions along various combinations of five variables. The first is gender (male, female). The second is age (18-29, 30-44, 45-59, 60 and over). The third is race/ethnicity (White, Black, other, Hispanic). The fourth is region (northeast, Midwest, south, west). Finally, the fifth variable is education (highest level achieved: less than high school, high school, some college, college degree or more). Similar distributions are calculated using the most recent U.S. Census Bureau's Current Popul\nation Survey data and the Knowledge Network panel data. Cell-by-cell adjustments over the various univariate and bivariate distributions are calculated to make the weighted sample cells match those of the U.S. Census and the Knowledge Network panel."},{"typeName":"responseRate","multiple":false,"typeClass":"primitive","value":"The response rate was 62.8%."}]}},"files":[{"description":"","label":"Threat_Perceptions_Codebook.pdf","restricted":false,"version":1,"datasetVersionId":43265,"dataFile":{"id":2300763,"persistentId":"doi:10.7910/DVN/KERPJC/WYIOLB","pidURL":"https://doi.org/10.7910/DVN/KERPJC/WYIOLB","filename":"Threat_Perceptions_Codebook.pdf","contentType":"application/pdf","friendlyType":"Adobe PDF","filesize":285371,"description":"","storageIdentifier":"s3://dvn-cloud:69563","rootDataFileId":-1,"md5":"e80e21a6621ec00f7ea74d047de657ea","checksum":{"type":"MD5","value":"e80e21a6621ec00f7ea74d047de657ea"},"tabularData":false,"creationDate":"2011-07-19","publicationDate":"2011-07-18","lastUpdateTime":"2011-07-19T18:22:45Z","fileAccessRequest":false}},{"description":"","label":"Threat_Perceptions_Data.tab","restricted":false,"version":1,"datasetVersionId":43265,"dataFile":{"id":2300759,"persistentId":"doi:10.7910/DVN/KERPJC/ISRVCO","pidURL":"https://doi.org/10.7910/DVN/KERPJC/ISRVCO","filename":"Threat_Perceptions_Data.tab","contentType":"text/tab-separated-values","friendlyType":"Tab-Delimited","filesize":272615,"description":"","storageIdentifier":"s3://dvn-cloud:69559","originalFileFormat":"application/x-spss-sav","originalFormatLabel":"SPSS Binary","originalFileSize":1093963,"originalFileName":"Threat_Perceptions_Data.sav","UNF":"UNF:5:KSpUdTV8nPBD5KgsY9gdqA==","rootDataFileId":-1,"md5":"2c863bd49f777c59c7100025606bf18d","checksum":{"type":"MD5","value":"2c863bd49f777c59c7100025606bf18d"},"tabularData":true,"creationDate":"2011-07-19","publicationDate":"2011-07-18","lastUpdateTime":"2011-07-19T18:22:45Z","fileAccessRequest":false}},{"description":"","label":"Threat_Perceptions_Questionnaire.pdf","restricted":false,"version":1,"datasetVersionId":43265,"dataFile":{"id":2300760,"persistentId":"doi:10.7910/DVN/KERPJC/JGCSVX","pidURL":"https://doi.org/10.7910/DVN/KERPJC/JGCSVX","filename":"Threat_Perceptions_Questionnaire.pdf","contentType":"application/pdf","friendlyType":"Adobe PDF","filesize":88846,"description":"","storageIdentifier":"s3://dvn-cloud:69560","rootDataFileId":-1,"md5":"e9c464186f3b04da3649c45fee7882b5","checksum":{"type":"MD5","value":"e9c464186f3b04da3649c45fee7882b5"},"tabularData":false,"creationDate":"2011-07-19","publicationDate":"2011-07-18","lastUpdateTime":"2011-07-19T18:22:45Z","fileAccessRequest":false}}]}}}