<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Assessing the Fairness of Rating Factors in Car Insurance and Lending</dcterms:title><dcterms:identifier>https://doi.org/10.7910/DVN/BKJ74X</dcterms:identifier><dcterms:creator>Kiviat, Barbara</dcterms:creator><dcterms:publisher>Harvard Dataverse</dcterms:publisher><dcterms:issued>2025-10-21</dcterms:issued><dcterms:modified>2025-10-21T21:56:48Z</dcterms:modified><dcterms:description>This dataset comes from a nationally representative online survey about the perceived fairness of using various sorts of personal information in the underwriting and pricing of car insurance and consumer loans. The data was collected by YouGov and partially paid for by the National Science Foundation (Doctoral Dissertation Research Improvement Award 1802286).</dcterms:description><dcterms:subject>Social Sciences</dcterms:subject><dcterms:isReferencedBy>Kiviat, Barbara. 2021. “Which Data Fairly Differentiate? American Views on the Use of Personal Data in Two Market Settings.” Sociological Science 8:26-47.</dcterms:isReferencedBy><dcterms:date>2025-10-21</dcterms:date><dcterms:contributor>Kiviat, Barbara</dcterms:contributor><dcterms:dateSubmitted>2025-10-21</dcterms:dateSubmitted><dcterms:license>CC0 1.0</dcterms:license></metadata>