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The code constructs the results from the field data and additional experiments we ran on Prolific and MTurk. The material contains 4 code files, all ending with “.do”. The code was last run using Stata (version 18.0) on MacOS. The replicator should expect the code to run under 5 minutes on a standard (2024) desktop machine.</p><p dir=\"ltr\"><b>Background</b> The spread of misinformation has been linked to increased social divisions and adverse health outcomes, but less is known about the production of disinformation, which is misinformation intended to mislead.</p><p dir=\"ltr\"><b>Method</b> The main data used in this paper has been collected by the authors using the Mturk interface (Field Experiment) or Qualtrics (Manipulation Check, Downstream Consequences, and Platform Interventions). It is available in the replication package. Our survey design and selection eligibility are included in the Supplementary Document in this depository.</p><p dir=\"ltr\"><b>Results</b> In a field experiment on MTurk (N=1,197), we found that while 70% of workers accepted a control job, 61% accepted a disinformation job requiring them to manipulate COVID-19 data. To quantify the trade-off between ethical and financial considerations in job acceptance, we introduced a lower-pay condition offering half the wage of the control job; 51% of workers accepted this job, suggesting that the ethical compromise in the disinformation task reduced the acceptance rate by about the same amount as a 25% wage reduction.</p><p dir=\"ltr\">A survey experiment with a nationally representative sample shows that viewing a disinformation graph from the field experiment negatively affected people’s beliefs and behavioral intentions related to the COVID-19 pandemic, including increased vaccine hesitancy.</p><p dir=\"ltr\"><b>Conclusion</b> Using a “wisdom-of-crowds” approach, we highlight how online labor markets can introduce features, such as increased worker accountability, to reduce the likelihood of workers engaging in the production of disinformation. Our findings emphasize the importance of addressing the supply side of disinformation in online labor markets to mitigate its harmful societal effects.</p>"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Other"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Disinformation"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Field Experiment"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Online Labor Markets"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Unethical Work"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Behavioural Economics"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"<p>This entry is a twenty-two-file data package totaling 9.2 MB, containing files in .txt, .pdf, .sav, .odt, .dta, .do, .csv and .ods formats.<p><p>If you use this dataset, please cite: Stoop, Jan; Cohn, Alain (2024). 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