Stephanie Eckman
Stephanie Eckman
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Position: Insights from Survey Methodology can Improve Training Data
Whether future AI models are fair, trustworthy, and aligned with the public’s interests rests in part on our ability to collect …
Stephanie Eckman
,
Barbara Plank
,
Frauke Kreuter
PDF
Project
DOI
Annotation Sensitivity: Training Data Collection Methods Affect Model Performance
When training data are collected from human annotators, the design of the annotation instrument, the instructions given to annotators, …
Christoph Kern
,
Stephanie Eckman
,
Jacob Beck
,
Rob Chew
,
Bolei Ma
,
Frauke Kreuter
PDF
Project
DOI
Underreporting of Purchases in the U.S. Consumer Expenditure Survey
Motivated misreporting occurs when respondents give incorrect responses to survey questions to shorten the interview; studies have …
Stephanie Eckman
PDF
Project
DOI
Motivated Misreporting in Smartphone Surveys
Filter questions are used to administer follow-up questions to eligible respondents while allowing respondents who are not eligible to …
Jessica Daikeler
,
Ruben Bach
,
Henning Silber
,
Stephanie Eckman
PDF
Project
DOI
Misreporting to Looping Questions in Surveys: Recall, Motivation and Burden
Looping questions are used to collect data about several similar events, such as employment spells, retirement accounts, or marriages. …
Stephanie Eckman
,
Frauke Kreuter
PDF
Project
DOI
Does the Inclusion of Non-Internet Households in a Web Panel Reduce Coverage Bias?
The LISS online panel has made extra efforts to recruit and retain households that were not regular users of the internet into the …
Stephanie Eckman
PDF
Project
DOI
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