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Addressing a crisis of generalizability with large-scale construct validation

Published online by Cambridge University Press:  10 February 2022

Jessica Kay Flake
Affiliation:
Department of Psychology, McGill University, Montreal, QCH3A 1G1, Canada. Jessica.flake@mcgill.ca; raymond.luong@mail.mcgill.ca; mairead.shaw@mail.mcgill.ca; https://www.mcgill.ca/psychology/jessica-kay-flake; https://www.mcgill.ca/psychology/jessica-kay-flake
Raymond Luong
Affiliation:
Department of Psychology, McGill University, Montreal, QCH3A 1G1, Canada. Jessica.flake@mcgill.ca; raymond.luong@mail.mcgill.ca; mairead.shaw@mail.mcgill.ca; https://www.mcgill.ca/psychology/jessica-kay-flake; https://www.mcgill.ca/psychology/jessica-kay-flake
Mairead Shaw
Affiliation:
Department of Psychology, McGill University, Montreal, QCH3A 1G1, Canada. Jessica.flake@mcgill.ca; raymond.luong@mail.mcgill.ca; mairead.shaw@mail.mcgill.ca; https://www.mcgill.ca/psychology/jessica-kay-flake; https://www.mcgill.ca/psychology/jessica-kay-flake

Abstract

Because of the misspecification of models and specificity of operationalizations, many studies produce claims of limited utility. We suggest a path forward that requires taking a few steps back. Researchers can retool large-scale replications to conduct the descriptive research which assesses the generalizability of constructs. Large-scale construct validation is feasible and a necessary next step in addressing the generalizability crisis.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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