{"id":"https://openalex.org/W4396498947","doi":"https://doi.org/10.1162/99608f92.79d4660d","title":"Noisy Measurements Are Important; The Design of Census Products Is Much More Important","display_name":"Noisy Measurements Are Important; The Design of Census Products Is Much More Important","publication_year":2024,"publication_date":"2024-04-30","ids":{"openalex":"https://openalex.org/W4396498947","doi":"https://doi.org/10.1162/99608f92.79d4660d"},"language":"en","primary_location":{"id":"doi:10.1162/99608f92.79d4660d","doi":"https://doi.org/10.1162/99608f92.79d4660d","is_oa":true,"landing_page_url":"https://doi.org/10.1162/99608f92.79d4660d","pdf_url":"https://hdsr.mitpress.mit.edu/pub/vctoo3sw/download/pdf","source":{"id":"https://openalex.org/S4306511929","display_name":"Harvard Data Science Review","issn_l":"2644-2353","issn":["2644-2353","2688-8513"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Harvard Data Science Review","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://hdsr.mitpress.mit.edu/pub/vctoo3sw/download/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080934644","display_name":"John Maron Abowd","orcid":"https://orcid.org/0000-0002-0998-4531","observed_orcids":["https://orcid.org/0000-0002-0998-4531"]},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"John M. Abowd","raw_affiliation_strings":["Cornell University, Ithaca, New York, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-0998-4531","affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, New York, United States of America","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5080934644"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":0.422,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.5795178,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"6","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13546","display_name":"Census and Population Estimation","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13030","display_name":"Survey Sampling and Estimation Techniques","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/differential-privacy","display_name":"differential privacy","score":0.8619999885559082},{"id":"https://openalex.org/keywords/2020-census","display_name":"2020 Census","score":0.9909999966621399},{"id":"https://openalex.org/keywords/disclosure-avoidance","display_name":"disclosure avoidance","score":0.7059999704360962},{"id":"https://openalex.org/keywords/query-workload","display_name":"query workload","score":0.6520000100135803},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.7269999980926514}],"concepts":[{"id":"https://openalex.org/C52130261","wikidata":"https://www.wikidata.org/wiki/Q39825","display_name":"Census","level":3,"score":0.8680011630058289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5933787226676941},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5462827086448669},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5265942811965942},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.516788125038147},{"id":"https://openalex.org/C15672241","wikidata":"https://www.wikidata.org/wiki/Q463769","display_name":"American Community Survey","level":4,"score":0.49312064051628113},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.47023528814315796},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.43511682748794556},{"id":"https://openalex.org/C2777886440","wikidata":"https://www.wikidata.org/wiki/Q15916459","display_name":"Plea","level":2,"score":0.4161134362220764},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.40380537509918213},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37302854657173157},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3489091992378235},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3420547842979431},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.15330541133880615},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.14393800497055054},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11868348717689514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11346974968910217},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.09850555658340454},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.09685656428337097},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0886278748512268},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1162/99608f92.79d4660d","doi":"https://doi.org/10.1162/99608f92.79d4660d","is_oa":true,"landing_page_url":"https://doi.org/10.1162/99608f92.79d4660d","pdf_url":"https://hdsr.mitpress.mit.edu/pub/vctoo3sw/download/pdf","source":{"id":"https://openalex.org/S4306511929","display_name":"Harvard Data Science Review","issn_l":"2644-2353","issn":["2644-2353","2688-8513"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Harvard Data Science Review","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:arx:papers:2312.14191","doi":null,"is_oa":false,"landing_page_url":"http://arxiv.org/pdf/2312.14191","pdf_url":"http://arxiv.org/pdf/2312.14191","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},{"id":"pmh:oai:arXiv.org:2312.14191","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.14191","pdf_url":"https://arxiv.org/pdf/2312.14191","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:53964e772d8e478aa84ff72305a72705","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/53964e772d8e478aa84ff72305a72705","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Harvard Data Science Review, Vol 6, Iss 2 (2024)","raw_type":"article"},{"id":"doi:10.48550/arxiv.2312.14191","doi":"https://doi.org/10.48550/arxiv.2312.14191","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2312.14191","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.1162/99608f92.79d4660d","doi":"https://doi.org/10.1162/99608f92.79d4660d","is_oa":true,"landing_page_url":"https://doi.org/10.1162/99608f92.79d4660d","pdf_url":"https://hdsr.mitpress.mit.edu/pub/vctoo3sw/download/pdf","source":{"id":"https://openalex.org/S4306511929","display_name":"Harvard Data Science Review","issn_l":"2644-2353","issn":["2644-2353","2688-8513"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Harvard Data Science Review","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396498947.pdf","grobid_xml":"https://content.openalex.org/works/W4396498947.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2057353990","https://openalex.org/W2896936987","https://openalex.org/W3103312471","https://openalex.org/W3210989924","https://openalex.org/W4212774754","https://openalex.org/W4246158632","https://openalex.org/W4285100324","https://openalex.org/W4295350465","https://openalex.org/W4395064700","https://openalex.org/W4396541581","https://openalex.org/W4401970896"],"related_works":["https://openalex.org/W4388186624","https://openalex.org/W3196790638","https://openalex.org/W3191791870","https://openalex.org/W4401970747","https://openalex.org/W4415932245","https://openalex.org/W4283376367","https://openalex.org/W3046830894","https://openalex.org/W2954085430","https://openalex.org/W3203236016","https://openalex.org/W4206996002"],"abstract_inverted_index":{"McCartan":[0],"et":[1],"al.":[2],"(2023)":[3],"call":[4],"for":[5,10,30,42,54,149],"\"making":[6],"differential":[7,50],"privacy":[8,51],"work":[9],"census":[11,70],"data":[12,71],"users.\"":[13],"This":[14],"commentary":[15],"explains":[16],"why":[17],"the":[18,27,45,49,55,59,62,66,74,79,102,109,112,123,144],"2020":[19,56,80],"Census":[20,57,81],"Noisy":[21],"Measurement":[22],"Files":[23],"(NMFs)":[24],"are":[25,88],"not":[26],"best":[28],"focus":[29],"that":[31,92],"plea.":[32],"The":[33,97],"August":[34],"2021":[35],"letter":[36],"from":[37,146],"62":[38],"prominent":[39],"researchers":[40],"asking":[41],"production":[43],"of":[44,48,61,68,91,143],"direct":[46,141],"output":[47],"system":[52],"deployed":[53],"signaled":[58],"engagement":[60],"scholarly":[63],"community":[64],"in":[65],"design":[67],"decennial":[69],"products.":[72],"NMFs,":[73],"raw":[75],"statistics":[76,106],"produced":[77],"by":[78],"Disclosure":[82],"Avoidance":[83],"System":[84],"before":[85],"any":[86],"post-processing,":[87],"one":[89],"component":[90,100],"design-the":[93],"query":[94,103,113],"strategy":[95],"output.":[96],"more":[98,128],"important":[99],"is":[101],"workload":[104],"output-the":[105],"released":[107],"to":[108,126],"public.":[110],"Optimizing":[111],"workload-the":[114],"Redistricting":[115],"Data":[116],"(P.L.":[117],"94-171)":[118],"Summary":[119],"File,":[120],"specifically-could":[121],"allow":[122],"privacy-loss":[124],"budget":[125],"be":[127,133],"effectively":[129],"managed.":[130],"There":[131],"could":[132],"fewer":[134],"noisy":[135],"measurements,":[136],"no":[137],"post-processing":[138],"bias,":[139],"and":[140],"estimates":[142],"uncertainty":[145],"disclosure":[147],"avoidance":[148],"each":[150],"published":[151],"statistic.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2024-05-01T00:00:00"}
