Replication Data for: Re-evaluating the impact of collective victimhood on conflict attitudes: Results from a natural experiment, a survey experiment, and panel study using Israel’s Holocaust Memorial Daydoi:10.7910/DVN/SKKYFBHarvard Dataverse2024-08-021Shelef, Nadav; vanderWilden, Ethan, 2024, "Replication Data for: Re-evaluating the impact of collective victimhood on conflict attitudes: Results from a natural experiment, a survey experiment, and panel study using Israel’s Holocaust Memorial Day", https://doi.org/10.7910/DVN/SKKYFB, Harvard Dataverse, V1, UNF:6:DpMwszkLERS73hja3oD0JQ== [fileUNF]Replication Data for: Re-evaluating the impact of collective victimhood on conflict attitudes: Results from a natural experiment, a survey experiment, and panel study using Israel’s Holocaust Memorial Daydoi:10.7910/DVN/SKKYFBShelef, NadavvanderWilden, EthanEthan vanderWildenHarvard DataverseEthan vanderWildenvanderWilden, EthanSocial SciencesHolocaustconflictIsraelnatural experimentcollective victimhoodA significant observational literature identifies a link between collective victimhood and conflict-enhancing attitudes, though results from experimental studies increasing victimhood’s salience vary. This article thus revisits this question in two studies in a context in which increased salience is especially likely to shift attitudes. Study 1 exploits the happenstance fielding of 12 surveys over Israel’s Holocaust Memorial Day between 1979 and 2021. Using all 192 available estimates assessing hawkishness, preferences for out-group exclusion, and in-group solidarity, it fails to detect statistically significant effects of a state-led effort to increase the salience of Israel’s collective victimhood narrative in a natural setting 90% of the time. Study 2 replicates the null findings across multiple comparisons and outcomes in a companion harmonized panel and survey experiment. Substantively, the findings suggest that it may be harder to use short-term manipulations of collective victimhood to shift attitudes than often assumed.This dataset underwent an independent verification process, complying with the AJPS Verification Policy updated June 2023, which replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of the code. The verification process was carried out by the Cornell Center for Social Sciences at Cornell University. <br></br> The associated article has been awarded the Open Materials Badge. Learn more about the Open Practice Badges from the <a href="https://www.cos.io/">Center for Open Science</a>. <br></br> <img src="https://socialsciences.cornell.edu/sites/default/files/2024-04/materials_large_color.png" alt="Open Materials Badge " width="60" height="60"> <br></br> Open Materials BadgeSee the Readme.txt file for the list of data sources and the codebooks in the codebook folder for dataset contents.The <i>American Journal of Political Science</i> and the Cornell Center for Social Sciences are not responsible for the accuracy or quality of data uploaded within the <i>AJPS</i> Dataverse, for the use of those data, or for interpretations or conclusions based on their use.This dataset is made available for replication and future use. Please contact the corresponding author (ethan.vanderwilden@wisc.edu) with further inquiries or clarifications.full_data.tab8083138text/tab-separated-valuesUNF:6:nMvczxV/OYHGnvVEc7Htwg==Compiled survey data across 12 years, used for natural experiments [Study 1]. Descriptions of data and variables in Section A.1 of SI file.full_survey.tab1249119text/tab-separated-valuesUNF:6:0zqi/nsw6LlHgbnm3IJ4Sw==Original dataset from survey experiment and panel study [Study 2]. Descriptions of the survey and variables in Section A.3.3 of SI file.gtrends.tab3118text/tab-separated-valuesUNF:6:Vj/rbL36b7w1jkCOuRv5RA==Data for Google Trends Analysis collected from Google by the authors.meta_analysis_data.tab99715text/tab-separated-valuesUNF:6:WbTBeqBRsy1TW9Ll+IV4wg==Data to generate publication bias figure (Figure 1)pooled_reg_robust.tab1366text/tab-separated-valuesUNF:6:Z4dCWqvSKewnhBHwjkfJxw==Regression outputs produced from '1.NE_regressions.R' - robust subgroup specificationspooled_reg.tab1368text/tab-separated-valuesUNF:6:9WxgEFzCKjoiaRwfZc0/hw==Regression outputs produced from '1.NE_regressions.R' - subgroup analysisresults1.tab17624text/tab-separated-valuesUNF:6:8rxJecE+l9nqS8i+GV4ujA==Regression outputs produced from '1.NE_regressions.R' - robust treatment specification 1results2.tab15824text/tab-separated-valuesUNF:6:G7VibGLBtxLbvkvg3DiWtA==Regression outputs produced from '1.NE_regressions.R' - robust treatment specification 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in full dataset and outputs regression information for natural experiments [Study 1]type/x-r-syntax2.NE_results.RProduces results [figures and tables] from natural experiments [Study 1] throughout the paper and SI.type/x-r-syntax3.NE_descriptives.RProduces descriptive information and statistics from natural experiments [Study 1] throughout the paper and SI.type/x-r-syntax4.publication_bias.RProduces figures and tables relating to possible publication bias in literature connecting collective victimhood and conflict-related attitudes.type/x-r-syntax5.original_survey_analysis.RProduces all results relating to the original survey experiment/panel study [Study 2]. type/x-r-syntaxcodebook_gtrends.pdfCodebook for Google Trends dataset (gtrends.csv)application/pdfcodebook_pub_bias.pdfCodebook for publication bias dataset (meta_analysis_data.csv)application/pdfcodebook_study1.pdfCodebook for Study 1 dataset (full_data.csv)application/pdfcodebook_study2.pdfCodebook for Study 2 dataset (full_survey.csv)application/pdffunctions_HMD.RWrites all functions used throughout the subsequent scripts. The script includes descriptions of each function, and comments throughout the code to explain how each function works. The file should be loaded at the start of each analysis script.type/x-r-syntaxHMD_supplementary_information.pdfOnline appendix file. Includes outputs (tables and figures), as well as descriptions of the data [Study 1 - A, Study 2 - C.3]application/pdfREADME.txtREADME file explaining (1) general workflow, and then describing (2) R scripts, (3) Data, and (4) Computing environmenttext/plainreplication.logLog file for R scripts (Scripts 2-5, excluding helper function file and regression script)text/plaintable figures (main text).docxOutputs: Tables and figures in the main textapplication/vnd.openxmlformats-officedocument.wordprocessingml.document