{"id":"https://openalex.org/W4411946085","doi":"https://doi.org/10.1145/3736252.3742614","title":"Alternates, Assemble! Selecting Optimal Alternates for Citizens\u2019 Assemblies","display_name":"Alternates, Assemble! Selecting Optimal Alternates for Citizens\u2019 Assemblies","publication_year":2025,"publication_date":"2025-07-02","ids":{"openalex":"https://openalex.org/W4411946085","doi":"https://doi.org/10.1145/3736252.3742614"},"language":"en","primary_location":{"id":"doi:10.1145/3736252.3742614","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3736252.3742614","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3736252.3742614","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM Conference on Economics and Computation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3736252.3742614","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117840471","display_name":"Angelos Assos","orcid":"https://orcid.org/0009-0006-2841-3511"},"institutions":[{"id":"https://openalex.org/I4210110987","display_name":"IIT@MIT","ror":"https://ror.org/01wp8zh54","country_code":"US","type":"facility","lineage":["https://openalex.org/I30771326","https://openalex.org/I4210110987"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Angelos Assos","raw_affiliation_strings":["MIT, Cambridge, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0009-0006-2841-3511","affiliations":[{"raw_affiliation_string":"MIT, Cambridge, Massachusetts, USA","institution_ids":["https://openalex.org/I4210110987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099447650","display_name":"Carmel Baharav","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Carmel Baharav","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":"https://orcid.org/0009-0004-3634-6721","affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058074172","display_name":"Bailey Flanigan","orcid":"https://orcid.org/0000-0002-7805-1989"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bailey Flanigan","raw_affiliation_strings":["Harvard University, Cambridge, USA"],"raw_orcid":"https://orcid.org/0000-0002-7805-1989","affiliations":[{"raw_affiliation_string":"Harvard University, Cambridge, USA","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041089506","display_name":"Ariel D. Procaccia","orcid":"https://orcid.org/0000-0002-8774-5827"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ariel Procaccia","raw_affiliation_strings":["Harvard University, Cambridge, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0000-0002-8774-5827","affiliations":[{"raw_affiliation_string":"Harvard University, Cambridge, Massachusetts, USA","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5117840471"],"corresponding_institution_ids":["https://openalex.org/I4210110987"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22049726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"719","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12288","display_name":"Optimization and Search Problems","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5670555830001831}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5670555830001831}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3736252.3742614","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3736252.3742614","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3736252.3742614","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM Conference on Economics and Computation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3736252.3742614","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3736252.3742614","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3736252.3742614","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM Conference on Economics and Computation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6792225654","display_name":null,"funder_award_id":"IIS-2229881","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G826810440","display_name":null,"funder_award_id":"2229881","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320334227","display_name":"Harvard Data Science Initiative, Harvard University","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411946085.pdf","grobid_xml":"https://content.openalex.org/works/W4411946085.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W2953097870","https://openalex.org/W3036859662","https://openalex.org/W3211613509","https://openalex.org/W4281382050","https://openalex.org/W4287755054","https://openalex.org/W4306405420","https://openalex.org/W4393147704","https://openalex.org/W4403511027","https://openalex.org/W4405464784","https://openalex.org/W6803606533","https://openalex.org/W6837955862","https://openalex.org/W6846807647"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Citizens'":[0],"assemblies":[1,21],"are":[2,42],"an":[3,36,64],"increasingly":[4],"influential":[5],"form":[6],"of":[7,19,26],"deliberative":[8],"democracy,":[9],"where":[10],"randomly":[11],"selected":[12],"people":[13],"discuss":[14],"policy":[15],"questions.":[16],"The":[17],"legitimacy":[18],"these":[20,56],"hinges":[22],"on":[23,95,104],"their":[24],"representation":[25,127],"the":[27,120],"broader":[28],"population,":[29],"but":[30,47],"participant":[31],"dropout":[32,78,108],"often":[33],"leads":[34],"to":[35,54,86,107,119],"unbalanced":[37],"composition.":[38],"In":[39],"practice,":[40],"dropouts":[41],"replaced":[43],"by":[44],"preselected":[45],"alternates,":[46],"existing":[48],"methods":[49],"do":[50],"not":[51],"address":[52,59],"how":[53],"choose":[55],"alternates.":[57,131],"To":[58],"this":[60],"gap,":[61],"we":[62],"introduce":[63],"optimization":[65],"framework":[66],"for":[67,100],"alternate":[68],"selection.":[69],"Our":[70,90],"algorithmic":[71],"approach,":[72],"which":[73],"leverages":[74],"learning-theoretic":[75],"machinery,":[76],"estimates":[77],"probabilities":[79],"using":[80,113],"historical":[81],"data":[82,115],"and":[83,103],"selects":[84],"alternates":[85],"minimize":[87],"expected":[88],"misrepresentation.":[89],"theoretical":[91],"bounds":[92],"provide":[93],"guarantees":[94],"sample":[96],"complexity":[97],"(with":[98],"implications":[99],"computational":[101],"efficiency)":[102],"loss":[105],"due":[106],"probability":[109],"mis-estimation.":[110],"Empirical":[111],"evaluation":[112],"real-world":[114],"demonstrates":[116],"that,":[117],"compared":[118],"status":[121],"quo,":[122],"our":[123],"method":[124],"significantly":[125],"improves":[126],"while":[128],"requiring":[129],"fewer":[130]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}