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While externality and free rider problems are common, particularly with environmental goods, in high mountain areas of developing nations, adverse weather, high altitudes, lack of infrastructure, and low government capacity combine to make solving them challenging. \nWe have conducted tourist surveys in 2022 and 2023 (N=335) in the Sagarmatha National Park in Nepal to measure tourists’ willingness to pay for plastic bottle deposits. 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We propose an original theoretical framework to investigate how changing incumbent priorities can shape the developmental and political effects of captured PIs. While patrons concerned with survival can force PIs to specialize in political activities, those pursuing regime consolidation may incentivize PIs to multitask, delivering developmental gains and political rewards. We deploy our framework to study Venezuela’s Communal Councils. Leveraging difference-in-differences analyses, an original survey of Council participants, and 51 interviews with government officials and grassroots Communal Council members, we find that Councils yielded both economic and political returns during an early period marked by political stability and regime consolidation. However, as Venezuela’s economic collapse pushed the government into an authoritarian survival mode, Councils became politically specialized. 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This is accompanied by all relevant .Rdata files, which contain the full workspace after running the code in these files. The corporate voting data and birthweight data, which are discussed and analyzed in Sections 4.1 and 4.2, are also included.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/DBUOQR","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-01T00:54:52Z","registered":"2026-05-01T20:48:56Z","published":null,"updated":"2026-05-01T20:48:56Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/zyxgzv","type":"dois","attributes":{"doi":"10.7910/dvn/zyxgzv","identifiers":[],"creators":[{"name":"Hung, Jason","nameType":"Personal","givenName":"Jason","familyName":"Hung","affiliation":["Internet Society"],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0267-3925","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Gen Z, Social Media, Society \u0026amp; Technology (Gen Z SMST) Dataset"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Medicine, Health and Life Sciences"},{"subject":"Social Sciences"}],"contributors":[{"name":"Hung, Jason","nameType":"Personal","givenName":"Jason","familyName":"Hung","affiliation":["Internet Society"],"contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-04-30","dateType":"Submitted"},{"date":"2026-05-01","dateType":"Available"},{"date":"2026-02-16/2026-04-30","dateType":"Collected"},{"date":"2026","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["113723","5409","244699","244699","35619","201013","3033"],"formats":["application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","text/x-python-script","text/tab-separated-values","text/tab-separated-values","text/x-python-script","application/pdf","text/markdown"],"version":"1.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"lang":"en","rights":"Creative Commons Attribution Non Commercial 4.0 International","rightsUri":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-nc-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The Gen Z, Social Media, Society \u0026amp; Technology (Gen Z SMST) dataset is a structured, longformat compilation of 742 statistics concerning the social-media practices, mental health, social values, work ethics, educational attitudes, generative AI use, and workplace expectations of Generation Z, extracted from eight authoritative survey reports published between 2024 and 2025 by Deloitte (Global Gen Z and Millennial Survey, 2024 and 2025, plus the 2024 Mental Health Deep Dive), Ofcom (Children and Parents 2024, Online Nation 2024 and 2025), and the Pew Research Centre (Americans' Social Media Use 2024 and Teens, Social Media and Technology 2024). Each record encodes a single statistic together with the metadata required to reproduce, situate, and verify it. The source report, the publication and fieldwork years, the geographic scope, the thematic topic, the disaggregating subgroup and its value, the numerical value and unit, an optional direct comparator (e.g., in the measurement of Gen Z’s attitudes on AI use compared to that of millennials, millennials are treated as the comparison group), the page number in the source, any direct quotation, and a flag where the depositor had a concern about the data. The dataset is intended for secondary and quantitative data analysis, comparative research, and triangulation across reports. The author deposits the Gen Z SMST dataset in multiple formats (.csv, .tab, .xlsx). Publishing the same dataset in multiple formats maximises the usability of Gen Z SMST. Moreover, all data are anonymised and depersonalised.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/ZYXGZV","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-04-30T06:14:38Z","registered":"2026-05-01T20:47:08Z","published":null,"updated":"2026-05-01T20:47:08Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/cwmczi","type":"dois","attributes":{"doi":"10.7910/dvn/cwmczi","identifiers":[],"creators":[{"name":"Hasan, Md Hasebul","nameType":"Personal","givenName":"Md Hasebul","familyName":"Hasan","affiliation":["University of Texas, Arlington"],"nameIdentifiers":[]}],"titles":[{"title":"DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Social Sciences"}],"contributors":[{"name":"Hasan, Md Hasebul","nameType":"Personal","givenName":"Md Hasebul","familyName":"Hasan","affiliation":["University of Texas at Arlington"],"contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-04-30","dateType":"Submitted"},{"date":"2026-05-01","dateType":"Available"},{"date":"2026","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["8834589"],"formats":["application/zip"],"version":"1.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"lang":"en","rights":"Creative Commons Zero v1.0 Universal","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc0-1.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"DeEscalWild is a large-scale, real-world benchmark dataset designed to facilitate automated de-escalation and crisis intervention training using Small Language Models (SLMs). 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