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Titel:

Comparing Human-Only, AI-Assisted, and AI-Led Teams on Assessing Research Reproducibility in Quantitative Social Science

Dokumenttyp:
I4R Discussion Paper Series
Autor(en):
Brodeur, Abel; Valenta, David; Marcoci, Alexandru; Aparicio, Juan P.; Mikola, Derek; Barbarioli, Bruno; Alexander, Rohan; Deer, Lachlan; Stafford, Tom; Vilhuber, Lars; Bensch, Gunther; Goldschmitt, Dirk; Gourdon-Kanhukamwe, Amélie; de Varda, Andrea Gregor; Grigoryeva, Idaliya; Gugushvili, Alexi; Fletcher, Aaron H. A.; Habermann, Florian; Hablicsek, Márton; Haddad, Joanne; Hall, Jonathan D.; Abdelhady, Mohamed; Hammar, Olle; Hassouneh, Malek; Hausladen, Carina I.; Hendrikse, Sophie C. F.; Hepplew...     »
Abstract:
This study evaluates the effectiveness of varying levels of human and artificial intelligence (AI) integration in reproducibility assessments of quantitative social science research. We computationally reproduced quantitative results from published articles in the social sciences with 288 researchers, randomly assigned to 103 teams across three groups - human-only teams, AI-assisted teams and teams whose task was to minimally guide an AI to conduct reproducibility checks (the "AI-led" approach)....     »
Stichworte:
330
Verlag / Institution:
Institute for Replication (I4R)
Verlagsort:
s.l.
Jahr:
2025
Sprache:
eng
WWW:
https://hdl.handle.net/10419/308508
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