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@article{ Hunter Childs2019,
 title = {Trust and Credibility in the U.S. Federal Statistical System},
 author = {Hunter Childs, Jennifer and Clark Fobia, Aleia and King, Ryan and Morales, Gerson},
 journal = {Survey Methods: Insights from the Field},
 pages = {1-10},
 year = {2019},
 issn = {2296-4754},
 doi = {https://doi.org/10.13094/SMIF-2019-00001},
 abstract = {The U.S. Federal Statistical System (FSS) is searching for ways to ensure high quality data in surveys, given
declines in response rates and the associated increase in operational costs. They are searching for ways to
address problems with public trust in the government, if these issues could hinder their efforts. To address these
concerns, the Census Bureau partnered with other federal statistical agencies to collect data to assess attitudes,
beliefs, and concerns the public may have regarding federal statistics and the agencies that collect them. This
public opinion data enables the FSS to better understand public perceptions, and provides guidance for
communicating with the public and for future planning of data collection. This paper examines the impact of various
factors on trust in the FSS, including attitudes (belief in credibility and transparency of federal statistics), and
behavior (use of federal statistics). This research supports Brackfield and Fellegi’s model of trust in official
statistics by providing evidence of a significant relationship between credibility of statistical products and trust in
statistics more generally (Brackfield 2011; Fellegi, 1996, 2004, 2010). These data also suggest that promoting trust
in statistical products could lead towards increased trust in the agencies that produce them.},
 keywords = {Zuverlässigkeit; official statistics; Datengewinnung; Datenqualität; measurement; trustworthiness; political governance; data quality; Messung; United States of America; confidence; Antwortverhalten; attitude; population; politische Steuerung; credibility; governance; amtliche Statistik; Governance; USA; Vertrauen; Glaubwürdigkeit; response behavior; Bevölkerung; data capture; Einstellung}}