Publication | Closed Access
Constraints on Generality (COG): A Proposed Addition to All Empirical Papers
951
Citations
14
References
2017
Year
EngineeringBehavioral Decision MakingField ExperimentStatistical FoundationCumulative ScienceQuasi-experimentResearch EthicsPsychologyCausal InferenceSocial SciencesTheoretical AnalysisCog StatementsBiasExperimental EconomicsStatisticsPsychological ScientistsSelection BiasModel TheoryBias DetectionExperimental PsychologyComplexity TheoryComplexity SciencePreregistration (Science)Automated ReasoningEmpirical PapersStatistical InferenceSurvey Methodology
Psychological scientists draw inferences about populations based on samples-of people, situations, and stimuli-from those populations. Yet, few papers identify their target populations, and even fewer justify how or why the tested samples are representative of broader populations. A cumulative science depends on accurately characterizing the generality of findings, but current publishing standards do not require authors to constrain their inferences, leaving readers to assume the broadest possible generalizations. We propose that the discussion section of all primary research articles specify Constraints on Generality (i.e., a "COG" statement) that identify and justify target populations for the reported findings. Explicitly defining the target populations will help other researchers to sample from the same populations when conducting a direct replication, and it could encourage follow-up studies that test the boundary conditions of the original finding. Universal adoption of COG statements would change publishing incentives to favor a more cumulative science.
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