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Rigorous exploration in a model-centric science via epistemic iteration.

Berna Devezer1, Erkan O Buzbas2

  • 1Department of Business, University of Idaho.

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Summary
This summary is machine-generated.

Psychology faces generalizability issues due to its current research methods. A shift to model-centric science, focusing on iterative model refinement, offers a transparent and efficient solution for understanding and improving research generalizability.

Keywords:
epistemic iterationexplorationgeneralizabilitymodel-centricmodelingresult-centric

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Area of Science:

  • Psychology
  • Scientific Methodology
  • Research Generalizability

Background:

  • Current psychological research paradigms struggle with generalizability.
  • Dichotomous results and rapid discovery models lack theoretical depth to address these issues.
  • Existing paradigms are insufficient for robustly understanding and solving generalizability problems.

Purpose of the Study:

  • Propose a paradigm shift towards model-centric science in psychology.
  • Enhance the understanding of generalizability sources through a new scientific approach.
  • Promote systematic exploration and advancement within the field.

Main Methods:

  • Introduce a model-centric scientific paradigm.
  • Emphasize iterative development and refinement of theoretical, empirical, and statistical models.
  • Highlight the communication and integration between different types of models.

Main Results:

  • A model-centric approach offers greater sophistication in addressing generalizability.
  • This paradigm facilitates transparent and efficient scientific activity.
  • Illustrates the practical application and potential of model-centric science.

Conclusions:

  • A paradigm shift to model-centric science is crucial for psychology.
  • Iterative model building and refinement enhance understanding of generalizability.
  • This approach promises to advance psychological science by improving research robustness.