Integrating Converging Evidence in Behavioral Sciences

Gary L. Brase is a professor in the Department of Psychological Sciences at Kansas State University, where he studies complex human decision-making using social, cognitive, and evolutionary theories.

• PrefaceAcknowledgements1. A Quick Guide to Multi-Level Converging Lines of EvidenceConverging lines of Evidence Multiple Levels of ExplanationThe MCL framework.Intentional Level Algorithmic LevelBiological Level Advantages of the framework Putting the framework to workWhere to go from hereReferences2. Historical and Philosophical Background of the MCL FrameworkConvergence and ConsistencyConverging Lines of EvidenceSchmitt and Pilcher’s Multiple Lines of EvidenceConsistency across Multiple LevelsGeneral Levels of ExplanationTinbergen’s four questionsMarr’s Levels of Explanation Prior Unification FrameworksUnifying psychology Unifying scienceSummary of Historical BackgroundPhilosophical Background and IssuesTruth and the Nature of RealityAgainst Realism in ScienceSupporting RealismConsistency of SciencesModularity, Consciousness, and Free WillConclusionInciting scientific revolutionsReferences3. Concerns, Digressions, and Extensions of the MCL FrameworkIntroductionThe Persistence of InertiaThe Parsimony versus Complexity Issue The Difficulty of InterdisciplinarityDo I really need evolution in this framework?How Many Levels of explanation?Intentional LevelAlgorithmic LevelBiological LevelHow many lines of evidence? and where?Can This Framework Provide a Score?How does this framework really lead to better hypotheses?Improve traditional hypothesis testingMove to Bayesian statistics Move to multiple hypothesesDoes this framework make research more replicable?Can this framework be manipulated?ConclusionReferences4. Quick Illustrative Examples of the MCL FrameworkLanguageLearned Taste AversionTerror Management Theory More ExamplesReasoning about Social ExchangesExploration versus exploitation in searchingSex Differences in WayfindingDiscussionReferences5. Rationality and Quantitative Reasoning, using the MCL FrameworkRationalityTwo Visions of RationalityConstrained Maximization and Dual-Process ModelsThe Bayesian Reasoning Crucible (part 1)Satisficing, Extended Adaptations Views, and Favored formats modelsThe Bayesian Reasoning Crucible (part 2)SummaryThe Intentional LevelTheoretical Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryPhylogenetic Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryThe Algorithmic LevelPsychological Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryDevelopmental Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryCross-Cultural Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryAncestral Environments Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryMedical Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryThe Biological LevelPhysiological Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryGenetic Evidence on the nature of quantitative reasoningConstrained maximization and dual-process modelsExtended adaptations and favored formats modelsSummaryConclusionReferences