{"data":[{"id":"10.7910/dvn/mvetgw","type":"dois","attributes":{"doi":"10.7910/dvn/mvetgw","identifiers":[{"identifier":"51827","identifierType":"MEL"}],"creators":[{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Timothy","familyName":"Manyise","name":"Manyise, Timothy","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1951-9892"}]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Nurulhuda","familyName":"Ahmad Fatan","name":"Ahmad Fatan, Nurulhuda","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3599-9892"}]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Matthew","familyName":"Owen","name":"Owen, Matthew","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0009-0006-6579-0973"}]},{"nameType":"Personal","affiliation":["International Center of Insect Physiology and Ecology - ICIPE"],"givenName":"Menaga","familyName":"Meenakshisundaram","name":"Meenakshisundaram, Menaga","nameIdentifiers":[]},{"nameType":"Personal","affiliation":["Value Plus Consultants"],"givenName":"Alex","familyName":"Rutto","name":"Rutto, Alex","nameIdentifiers":[]}],"titles":[{"title":"Characterization of the practices and utilization of fish feed ingredients among fish farmers in Kenya"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Agricultural Sciences"},{"subject":"household survey"},{"subject":"baseline study"},{"subject":"small scale quaculture"},{"subject":"kenya aquaculture"},{"subject":"fish feed"}],"contributors":[{"nameType":"Personal","name":"WorldFish","contributorType":"Producer","affiliation":[],"nameIdentifiers":[]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Timothy","familyName":"Manyise","name":"Manyise, Timothy","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2025-12-31","dateType":"Created"},{"date":"2026-01-16","dateType":"Submitted"},{"date":"2026-01-15","dateType":"Available"},{"date":"2026-11-02","dateType":"Updated"},{"date":"2025-07-01/2025-09-30","dateType":"Other","dateInformation":"Time period covered by the data"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"Survey Data"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["617957","1882207"],"formats":["application/pdf","application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"],"version":"1.2","rightsList":[{"rightsUri":"info:eu-repo/semantics/closedAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","lang":"en","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The sustainable growth of aquaculture in sub-Saharan Africa depends critically on the availability of affordable, nutritious fish feeds and the adoption of appropriate feeding practices. In support of this objective, WorldFish is implementing a five-year initiative titled Development and Scaling of Sustainable Feeds for Resilient Aquatic Food Systems in Sub-Saharan Africa (FASA), funded by the Norwegian Agency for Development Cooperation (Norad). The project aims to develop and scale locally appropriate feed solutions to enhance productivity, resilience, and livelihoods among smallholder aquaculture producers.\n\nThis dataset presents baseline survey data collected from 846 smallholder fish farmers in Kenya to inform the design, implementation, and evaluation of FASA interventions. The survey covers both grow-out and hatchery operations across nine counties, including six counties in the Lake Victoria region (Kakamega, Busia, Kisumu, Siaya, Migori, and Homa Bay) and three coastal counties (Kwale, Kilifi, and Mombasa). Data were collected using a structured questionnaire administered through face-to-face interviews.\n\nThe dataset contains detailed information on farmers’ socio-economic characteristics, aquaculture production systems, feeding and feed management practices, access to and use of locally available feed ingredients, feed sourcing and costs, knowledge and awareness of alternative feed options, and constraints to adoption. Additional variables capture institutional access, extension services, and market-related factors influencing feed use decisions.\n\nThis dataset provides a robust empirical foundation for analyzing determinants of feed access and utilization, identifying barriers to the uptake of locally available feed ingredients, and establishing benchmark indicators for monitoring change over the life of the FASA project. Beyond project monitoring and evaluation, the dataset is relevant for researchers, policymakers, and development practitioners interested in aquaculture feed systems, smallholder productivity, and sustainable aquatic food system transformation in sub-Saharan Africa."},{"descriptionType":"Other","description":"Type: Dataset; Sub-type(s): Survey Data"}],"geoLocations":[{"geoLocationPlace":"Kenya"}],"fundingReferences":[{"funderName":"Norwegian Agency for Development Cooperation - NORAD"}],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/MVETGW","contentUrl":null,"metadataVersion":4,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":79,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-01-16T04:18:06Z","registered":"2026-01-16T04:24:45Z","published":null,"updated":"2026-11-02T08:48:41Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/pchisz","type":"dois","attributes":{"doi":"10.7910/dvn/pchisz","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["University of Helsinki"],"givenName":"Jorma","familyName":"Valjakka","name":"Valjakka, Jorma","nameIdentifiers":[]},{"nameType":"Personal","affiliation":["University of Helsinki"],"givenName":"Juhani","familyName":"Kivimäki","name":"Kivimäki, Juhani","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9673-9760"}]},{"nameType":"Personal","affiliation":["University of Helsinki"],"givenName":"Juha","familyName":"Mylläri","name":"Mylläri, Juha","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0009-0002-0480-4623"}]},{"nameType":"Personal","affiliation":["University of Helsinki"],"givenName":"Jukka","familyName":"Nurminen","name":"Nurminen, Jukka","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5083-1927"}]}],"titles":[{"title":"The Labeling Problem in Hallucination Detection Benchmarks: human-judge release dataset"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Computer and Information Science"}],"contributors":[{"nameType":"Personal","affiliation":["University of Helsinki"],"givenName":"Jorma","familyName":"Valjakka","name":"Valjakka, Jorma","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-10-05","dateType":"Available"},{"date":"2026-11-02","dateType":"Updated"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["10850","1130544","19312","58257","19277","58257","58324","1143773","20713","11387","60372"],"formats":["text/tab-separated-values","text/tab-separated-values","text/markdown","application/json","text/markdown","application/json","application/json","text/tab-separated-values","text/markdown","text/tab-separated-values","application/json"],"version":"4.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution Share Alike 4.0 International","lang":"en","rightsIdentifier":"cc-by-sa-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"This dataset contains generated answers from multiple large language models for open-domain question-answering benchmarks, together with primary human hallucination labels, optional second-annotator labels, automatic LLM-judge labels, and lexical/NLI baseline outputs. Each row corresponds to one generated answer for one question by one generator model. The dataset is intended to support reproducible analysis of human-vs-automatic hallucination labeling, prompt variants for LLM-as-a-judge evaluation, and baseline comparisons. The human annotations, judge labels, metric scores and documentation are released under CC BY-SA 4.0; the model-generated answers in the answer_text column remain subject to the terms of the respective generation models (see the License section of README.md)."}],"geoLocations":[],"fundingReferences":[{"funderName":"https://ror.org/05bgf9v38","awardNumber":"23004 ELFMo (ITEA4)"}],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/PCHISZ","contentUrl":null,"metadataVersion":4,"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":"2026-05-05T14:48:58Z","registered":"2026-10-05T11:11:23Z","published":null,"updated":"2026-11-02T08:43:03Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/ohkcyl","type":"dois","attributes":{"doi":"10.7910/dvn/ohkcyl","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["Yaşar University"],"givenName":"YASİN","familyName":"ÖZARSLAN","name":"ÖZARSLAN, YASİN","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0831-6985"}]}],"titles":[{"title":"xLEARN"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Computer and Information Science"},{"subject":"Social Sciences"}],"contributors":[{"nameType":"Personal","affiliation":["Yaşar University"],"givenName":"YASİN","familyName":"ÖZARSLAN","name":"ÖZARSLAN, YASİN","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-08-12","dateType":"Submitted"},{"date":"2026-08-14","dateType":"Available"},{"date":"2026-11-02","dateType":"Updated"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["29897","289012","499854","832037","399","6750544","1661338982","117225","29499","20113","28671"],"formats":["application/zip","text/tab-separated-values","text/tab-separated-values","text/tab-separated-values","text/tab-separated-values","text/tab-separated-values","application/zip","application/pdf","application/vnd.openxmlformats-officedocument.wordprocessingml.document","application/zip","application/vnd.openxmlformats-officedocument.wordprocessingml.document"],"version":"2.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/restrictedAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","lang":"en","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"\u0026lt;p\u0026gt;xLEARN is a large-scale, longitudinal dataset of event-level xAPI learning experience data with academic context in higher education. The dataset was extracted from the Learning Management System (Sakai CLE) of Yaşar University and integrated with institutional records from the Student Information System (SIS). It contains 17,026,443 xAPI statements, 9,358 student accounts, 8 standardized xAPI verbs, 4,431 course offerings, 9,358 student records, and 114,152 final grade records, covering six academic terms (Fall 2019 to Summer 2021). Interaction records were collected between 16 March 2020 and August 2021; for courses of the Fall 2019 term, only interactions recorded after the end of the term are included.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;The dataset combines fine-grained behavioral interaction records with contextual academic information, including pseudonymized student attributes (education level, faculty, program duration), course metadata, and final course grades. Each xAPI statement includes the actor, verb, object, timestamp, context, and associated metadata, including the complete nested JSON representation stored in the \u0026lt;code\u0026gt;full_statement\u0026lt;/code\u0026gt; field. The contextual data are distributed as separate CSV files and can be linked to interaction records through shared pseudonymized identifiers such as \u0026lt;code\u0026gt;account_name\u0026lt;/code\u0026gt;, \u0026lt;code\u0026gt;site_id\u0026lt;/code\u0026gt;, and \u0026lt;code\u0026gt;verb_id\u0026lt;/code\u0026gt;. Only student accounts are included; instructor accounts and their statements were removed before release.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;The data package consists of Learning Record Store (LRS) data, Student Information System (SIS) data, validation scripts, documentation, and the Data Use Agreement. The primary data files are \u0026lt;code\u0026gt;lrs_statements.csv\u0026lt;/code\u0026gt;, \u0026lt;code\u0026gt;lrs_agents.csv\u0026lt;/code\u0026gt;, \u0026lt;code\u0026gt;lrs_verbs.csv\u0026lt;/code\u0026gt;, \u0026lt;code\u0026gt;sis_students.csv\u0026lt;/code\u0026gt;, \u0026lt;code\u0026gt;sis_courses.csv\u0026lt;/code\u0026gt;, and \u0026lt;code\u0026gt;sis_final_grades.csv\u0026lt;/code\u0026gt;.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;All direct personal identifiers were removed, and consistent pseudonymized identifiers were applied before release; no mapping between original and pseudonymized identifiers was retained. The dataset uses UTF-8 encoded CSV files, timestamps with timezone information, and xAPI statements (version 1.0; the \u0026lt;code\u0026gt;version\u0026lt;/code\u0026gt; field of the statements records 1.0.0). Grades are reported on a 0–100 scale; NULL values in the \u0026lt;code\u0026gt;final_grade\u0026lt;/code\u0026gt; field correspond to non-graded enrollments, pass/fail options, or approved course withdrawals.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;A 10-step validation workflow was applied to assess data quality: duplicate detection, referential integrity, temporal consistency, missing value analysis, data sanity checks, verb–activity compliance, cross-source consistency, record completeness, user mapping verification, and JSON validity of the xAPI payloads. No duplicate identifiers, invalid references, timestamp inconsistencies, out-of-range values, or invalid JSON structures were found, and all statements and grade records are linked to valid students. 730,667 statements (4.3%) refer to LMS sites that have no record in \u0026lt;code\u0026gt;sis_courses.csv\u0026lt;/code\u0026gt; (for example personal workspaces) and were retained.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;The dataset contains the LMS events that Sakai CLE converts into xAPI statements; events not covered by these mapping rules are not included. It does not include activities occurring outside the LMS, and timestamps should be interpreted as recorded system interactions rather than direct measures of cognitive engagement or task duration. Because no derived features are provided, researchers are expected to define their own preprocessing, aggregation, feature construction, and modeling procedures according to their research objectives.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;The xLEARN dataset is available under controlled access. To obtain the individual-level files, researchers submit an access request through Harvard Dataverse and return the signed Data Use Agreement (DUA) to the data custodians from an institutional e-mail address; access is granted after verification of the institutional affiliation and approval by the data custodians. The documentation, the data dictionary, the DUA, the validation scripts, the course table, and the verb table are provided openly to support transparency, reproducibility, and data reuse.\u0026lt;/p\u0026gt;"}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/OHKCYL","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":15,"downloadCount":1,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-08-12T10:42:13Z","registered":"2026-08-14T16:46:23Z","published":null,"updated":"2026-11-02T08:25:22Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/iquwcj","type":"dois","attributes":{"doi":"10.7910/dvn/iquwcj","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Alex","familyName":"Tilley","name":"Tilley, Alex","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6363-0945"}]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Joctan","familyName":"Dos Reis Lopes","name":"Dos Reis Lopes, Joctan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4437-1044"}]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Fernando","familyName":"Cagua","name":"Cagua, Fernando","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5867-3687"}]},{"nameType":"Personal","affiliation":["WorldFish"],"givenName":"Lorenzo","familyName":"Longobardi","name":"Longobardi, Lorenzo","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3126-7341"}]}],"titles":[{"title":"Peskas Timor-Leste: small-scale fisheries landings"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Agricultural Sciences"},{"subject":"Earth and Environmental Sciences"},{"subject":"small-scale fisheries"},{"subject":"fisheries monitoring"},{"subject":"fish landings"},{"subject":"catch"},{"subject":"fishing effort"},{"subject":"Timor-Leste"},{"subject":"Peskas"}],"contributors":[{"nameType":"Personal","name":"WorldFish","contributorType":"Producer","affiliation":[],"nameIdentifiers":[]},{"nameType":"Personal","affiliation":["WorldFish"],"name":"Peskas team","contributorType":"ContactPerson","nameIdentifiers":[]},{"nameType":"Organizational","name":"Ministry of Agriculture and Fisheries, Timor-Leste","contributorType":"DataCollector","affiliation":[],"nameIdentifiers":[]}],"dates":[{"date":"2026-10-08","dateType":"Available"},{"date":"2026-11-02","dateType":"Updated"},{"date":"2017-07-02/2026-10-30","dateType":"Other","dateInformation":"Time period covered by the data"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"Survey data"},"relatedIdentifiers":[{"relationType":"References","relatedIdentifier":"10.1371/journal.pone.0234760","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["29807301","12267","27137346","12267","27141179","12267","27276611","12327"],"formats":["text/tab-separated-values","text/markdown","text/tab-separated-values","text/markdown","text/tab-separated-values","text/markdown","text/tab-separated-values","text/markdown"],"version":"4.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution Non Commercial Share Alike 4.0 International","lang":"en","rightsIdentifier":"cc-by-nc-sa-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"\u0026lt;p\u0026gt;Records of small-scale fishing trips landed around Timor-Leste, collected for \u0026lt;a href=\"https://timor.peskas.org\"\u0026gt;Peskas Timor-Leste\u0026lt;/a\u0026gt;, the country's official national fisheries monitoring system. Enumerators working with the Ministry of Agriculture and Fisheries record landings at landing sites with KoboToolbox: date, place, crew size, trip duration, gear, boat, habitat, and for each catch the species, length, estimated weight and value.\u0026lt;/p\u0026gt;\u0026lt;p\u0026gt;One row is one catch from one fishing trip. The table has passed automated checks and is the one the \u0026lt;a href=\"https://api.peskas.org/docs\"\u0026gt;Peskas Fishery Data API\u0026lt;/a\u0026gt; serves for Timor-Leste as validated landings. A new version is published every month under the same DOI, each holding the whole table from 2017 onwards.\u0026lt;/p\u0026gt;\u0026lt;p\u0026gt;README.md describes every column, how the data is produced and its limits. Releases from March 2022 to June 2025 are separate datasets in the \u0026lt;a href=\"https://dataverse.harvard.edu/dataverse/peskas\"\u0026gt;Peskas collection\u0026lt;/a\u0026gt;, with different files.\u0026lt;/p\u0026gt;"},{"descriptionType":"TechnicalInfo","description":"peskas.timor.data.pipeline, 5.8.1"},{"descriptionType":"Other","description":"Published automatically on the first day of each month. Catch weights are estimated from fish counts and lengths, not weighed. 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Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"\u0026lt;h3\u0026gt;LocalView is a database co-created by \u0026lt;a href:\"mailto:sbarari@g.harvard.edu\"\u0026gt;Soubhik Barari\u0026lt;/a\u0026gt;, \u0026lt;a href=\"mailto:tsimko@umich.edu\"\u0026gt;Tyler Simko\u0026lt;/a\u0026gt;, and \u0026lt;a href=\"mailto:mpreece@mit.edu\"\u0026gt;Mason Reece\u0026lt;/a\u0026gt; to advance the study of local government in the United States.\u0026lt;/h3\u0026gt;\u0026lt;br\u0026gt;\n\nIt is the \u0026lt;i\u0026gt;largest existing dataset of local government public meetings\u0026lt;/i\u0026gt;— the central policy-making process in American local government — as they are captured on video. \u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nTo get started, select the file(s) that you'd like for your use case based on the year that the meeting took place. Note: we are no longer supporting file formats other than \u0026lt;code\u0026gt;.parquet\u0026lt;/code\u0026gt; for space considerations. \u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nFor potential use cases or further guidance on downloading the data in bulk, visit the companion website: \u0026lt;a href=\"https://www.localview.net\"\u0026gt;localview.net\u0026lt;/a\u0026gt;.\n\n\u0026lt;h1\u0026gt;Change Log\u0026lt;/h1\u0026gt;\n\n\u0026lt;p\u0026gt;Scraping, parsing, identifying, and merging together meetings\ninvolves a large number of non-trivial decisions, many of which need to\nbe adjusted over time particularly as the YouTube API changes.\u0026lt;/p\u0026gt;\n\n\u0026lt;p\u0026gt;As such, when such decisions notably deviate from process or the\noutputs documented in the \u0026lt;a href=\"https://soubhikbarari.com/writings/localview.pdf\"\u0026gt;first version of\nthis database\u0026lt;/a\u0026gt;, it will be logged here.\u0026lt;/p\u0026gt;\n\n\u0026lt;div id=\"version-3.0-2026-05\" class=\"section level2\"\u0026gt;\n \u0026lt;h2\u0026gt;Version 3.0 (2026-05)\u0026lt;/h2\u0026gt;\n\n \u0026lt;ul\u0026gt;\n \u0026lt;li\u0026gt;\n Data updated until November 2025. Moving forward, data will be automatically updated to always be six months behind present.\n \u0026lt;/li\u0026gt;\n\n \u0026lt;li\u0026gt;\n Some new channels have been added. Please reach out to us via email if there are new local meeting channels not featured that we should include.\n \u0026lt;/li\u0026gt;\n\n \u0026lt;li\u0026gt;\n Codebook has been updated and simplified. ACS related columns have been removed.\n \u0026lt;/li\u0026gt;\n\n \u0026lt;li\u0026gt;\n Data format has been modified to separate transcripts from metadata\n \u0026lt;ul\u0026gt;\n \u0026lt;li\u0026gt;\n First, download \u0026lt;code\u0026gt;meta_localview.parquet\u0026lt;/code\u0026gt;, then filter to the channels and/or videos of interest.\n \u0026lt;/li\u0026gt;\n \u0026lt;li\u0026gt;\n Then, merge in transcripts as desired from \u0026lt;code\u0026gt;transcripts_localview_*.zip\u0026lt;/code\u0026gt;. Transcript file names are identified as \"\u0026lt;code\u0026gt;channel_id\u0026lt;/code\u0026gt;__\u0026lt;code\u0026gt;id\u0026lt;/code\u0026gt;.txt.gz\".\n \u0026lt;/li\u0026gt;\n \u0026lt;li\u0026gt;\n The transcript files have been separated into two parts only because of Dataverse size constraints, otherwise they are identical.\n \u0026lt;/li\u0026gt;\n \u0026lt;/ul\u0026gt;\n \u0026lt;/li\u0026gt;\n \u0026lt;/ul\u0026gt;\n\u0026lt;/div\u0026gt;\n\n\u0026lt;div id=\"version-2.0-2023-10\" class=\"section level2\"\u0026gt;\n\u0026lt;h2\u0026gt;Version 2.0 (2023-10)\u0026lt;/h2\u0026gt;\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;Data updated up until September 2023.\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;~10,000 new videos added, all belonging to existing channels in\ndatabase.\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Change in data format:\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;channelType\u0026lt;/code\u0026gt; column changed to\n\u0026lt;code\u0026gt;channel_type\u0026lt;/code\u0026gt;.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;ST_FIPS\u0026lt;/code\u0026gt; correctly padded to be 7 characters (2 digit\nstate code + 5 digit place FIPS code).\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;videos with no caption available from YouTube are explicitly marked\nas “\u0026lt;No caption available\u0026gt;” in \u0026lt;code\u0026gt;caption_text\u0026lt;/code\u0026gt;.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;caption_text_cleaned\u0026lt;/code\u0026gt; is actually consistently cleaned\n(previously stray timestamps/pause markers in some entries).\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_2018_*\u0026lt;/code\u0026gt; columns now prefixed as\n\u0026lt;code\u0026gt;acs_18\u0026lt;/code\u0026gt;.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;additional ACS variables now available for each place:\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_median_gross_rent\u0026lt;/code\u0026gt;: Median gross rent in FIPS\nplace.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_median_hh_inc\u0026lt;/code\u0026gt;: Median household income in FIPS\nplace.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_median_age\u0026lt;/code\u0026gt;: Median age in FIPS place.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_amind\u0026lt;/code\u0026gt;: American Indian population in FIPS\nplace.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_asian\u0026lt;/code\u0026gt;: Asian population in FIPS place.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;acs_18_nhapi\u0026lt;/code\u0026gt;: Native Hawaiian or Pacific Islander\npopulation in FIPS place.\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;\u0026lt;code\u0026gt;census_2015_*\u0026lt;/code\u0026gt; columns removed for redundancy.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;to avoid confusion and possible conflicts, \u0026lt;code\u0026gt;.json\u0026lt;/code\u0026gt; and\n\u0026lt;code\u0026gt;.csv\u0026lt;/code\u0026gt; file formats eliminated in favor of\n\u0026lt;code\u0026gt;.parquet\u0026lt;/code\u0026gt; format.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;municipal voteshare (\u0026lt;code\u0026gt;_dem2pv\u0026lt;/code\u0026gt;) variables have been\nremoved from the public use files for a number of reasons: (1) high\ndegree of missingness, (2) no columns estimates available, (3) potential\nsensitivity\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;The matching process of videos to ST-FIPS and government types is as\nfollows:\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;videos are matched to channels’ previous ST-FIPS codes and/or\ngovernment types \u0026lt;em\u0026gt;if\u0026lt;/em\u0026gt; there is an umambiguous match, otherwise a\n(1) series of regex matches with video title/description are used to\nattempt to match video to the government and (2) state/place names are\nextracted from each video’s title/description/caption and used to match\nto an ST-FIPS entity \u0026lt;em\u0026gt;if\u0026lt;/em\u0026gt; an unambiguous match; only identified\nvideos are then uploaded to the database.\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;to identify the date of the meeting that the video captures, we\nfirst try to extract the date from the title, otherwise we try to\nextract the date from the description, otherwise it is discarded.\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\n\u0026lt;/div\u0026gt;\n\u0026lt;div id=\"version-1.0-2023-02\" class=\"section level2\"\u0026gt;\n\u0026lt;h2\u0026gt;Version 1.0 (2023-02)\u0026lt;/h2\u0026gt;\n\u0026lt;p\u0026gt;See \u0026lt;a href=\"https://soubhikbarari.com/writings/localview.pdf\"\u0026gt;publication\u0026lt;/a\u0026gt;\nfor full details on methodology choices for the Version 1.0\ndatabase.\u0026lt;/p\u0026gt;\n\u0026lt;/div\u0026gt;\n\u0026lt;/div\u0026gt;"}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/NJTBEM","contentUrl":null,"metadataVersion":22,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":5445,"downloadCount":1046,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-01-13T18:59:25Z","registered":"2023-01-13T19:12:09Z","published":null,"updated":"2026-11-02T04:30:19Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/tuc2qi","type":"dois","attributes":{"doi":"10.7910/dvn/tuc2qi","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["University of Alaska Statewide System"],"givenName":"Russell","familyName":"Luke","name":"Luke, Russell","nameIdentifiers":[]}],"titles":[{"title":"Replication Data for - The Effects of Alaska’s Electoral Reforms: Third-Party and Nonpartisan Candidate Participation and Performance"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Social Sciences"}],"contributors":[{"nameType":"Personal","affiliation":["University of Alaska Statewide System"],"givenName":"Russell","familyName":"Luke","name":"Luke, Russell","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-11-01","dateType":"Submitted"},{"date":"2026-11-01","dateType":"Available"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["41122","35915","15029232","71075","102314"],"formats":["type/x-r-syntax","application/x-rlang-transport","application/x-rlang-transport","type/x-r-syntax","application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"],"version":"1.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Data and code used for all tables and figures in The Effects of Alaska’s Electoral Reforms: Third-Party and Nonpartisan Candidate Participation and Performance - both manuscript and online appendix"}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TUC2QI","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":"2026-11-02T03:28:19Z","registered":"2026-11-02T03:28:41Z","published":null,"updated":"2026-11-02T03:28:41Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/abti18","type":"dois","attributes":{"doi":"10.7910/dvn/abti18","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["Claremont Graduate University"],"givenName":"Carlos","familyName":"Algara","name":"Algara, Carlos","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7820-9109"}]},{"nameType":"Personal","affiliation":["Occidental College"],"givenName":"Isaac","familyName":"Hale","name":"Hale, Isaac","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3664-5949"}]},{"nameType":"Personal","affiliation":["Claremont Graduate University"],"givenName":"Byengseon","familyName":"Bae","name":"Bae, Byengseon","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8540-5247"}]}],"titles":[{"title":"Replication Data for: Taking the Median Voter Seriously: Experimental \u0026amp; 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Overall, these findings demonstrate the immunoprotective potential of detoxified C. perfringens α-toxin, highlighting the application value of the microbial components for combating infectious diseases."}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/HSVURR","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":9,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-07-20T02:14:06Z","registered":"2026-07-29T20:27:37Z","published":null,"updated":"2026-11-02T00:24:09Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}},{"id":"10.7910/dvn/3liib9","type":"dois","attributes":{"doi":"10.7910/dvn/3liib9","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["Independent Researcher"],"givenName":"Sinclair(Po-Sung)","familyName":"Huang","name":"Huang, Sinclair(Po-Sung)","nameIdentifiers":[]}],"titles":[{"title":"Replication Data for: From Plausible Explanation to Physical Verification: Evidence-to-Action Gates in AI-Assisted Automotive Diagnosis"}],"publisher":"Harvard Dataverse","container":{},"publicationYear":2026,"subjects":[{"subject":"Computer and Information Science"},{"subject":"Human–AI Collaboration"},{"subject":"Generative AI"},{"subject":"Physical AI"},{"subject":"Process Tracing"},{"subject":"Automotive Diagnostics"},{"subject":"Evidence-to-Action Gates"},{"subject":"Reproducibility"}],"contributors":[{"nameType":"Personal","affiliation":["Independent Researcher"],"givenName":"Sinclair(Po-Sung)","familyName":"Huang","name":"Huang, Sinclair(Po-Sung)","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2026-10-27","dateType":"Submitted"},{"date":"2026-11-01","dateType":"Available"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["11568571"],"formats":["application/zip"],"version":"1.0","rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"rightsUri":"https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/3LIIB9","rights":"Custom terms specific to this dataset"}],"descriptions":[{"descriptionType":"Abstract","description":"This dataset contains the public replication materials accompanying the working paper *From Plausible Explanation to Physical Verification: Evidence-to-Action Gates in AI-Assisted Automotive Diagnosis* by Sinclair (Po-Sung) Huang.\u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nThe study examines human–AI collaboration in real-world automotive diagnosis through a longitudinal, retrospective single-case analysis. It investigates how AI-generated explanations, uncertainty, physical verification, and human judgment interact before consequential maintenance and procurement decisions.\u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nThe replication package includes de-identified evidence-ledger extracts, provisional transcript coding tables, four smartphone accelerometer recordings comprising 468,355 samples, Python analysis scripts, reproducibility checks, and supporting documentation.\u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nThe materials support independent computational reproduction of the reported analyses, but do not constitute independent validation of the vehicle's mechanical condition or the qualitative coding.\u0026lt;br\u0026gt;\u0026lt;br\u0026gt;\n\nPrivate workshop communications, personally identifying vehicle information, confidential source mappings, and location-sensitive follow-up measurements are excluded from the public release."}],"geoLocations":[],"fundingReferences":[],"url":"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/3LIIB9","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":"2026-10-27T15:55:03Z","registered":"2026-11-02T00:21:32Z","published":null,"updated":"2026-11-02T00:21:32Z"},"relationships":{"client":{"data":{"id":"gdcc.harvard-dv","type":"clients"}}}}],"meta":{"total":820512,"totalPages":400,"page":1},"links":{"self":"https://api.datacite.org/dois/?client-id=gdcc.harvard-dv","next":"https://api.datacite.org/dois?client-id=gdcc.harvard-dv\u0026page%5Bnumber%5D=2\u0026page%5Bsize%5D=25"}}