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Summary
This summary is machine-generated.

Human beliefs resist contradictory evidence due to auxiliary hypotheses. These rational "protective belts" link ideas and data, explaining away disconfirmation and maintaining belief robustness.

Keywords:
Bayesian modelingComputational learning theoriesPhilosophy of science

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Area of Science:

  • Cognitive Science
  • Philosophy of Science
  • Bayesian Cognition

Background:

  • Human beliefs often display remarkable robustness against disconfirming evidence.
  • This robustness is frequently attributed to cognitive shortcuts like heuristics or motivated reasoning.

Purpose of the Study:

  • To explore how auxiliary hypotheses contribute to belief robustness.
  • To demonstrate the wide-ranging implications of auxiliary hypotheses across different fields.

Main Methods:

  • Tracing the concept of auxiliary hypotheses from philosophy of science.
  • Applying Bayesian models to understand their role in cognition.
  • Analyzing behavioral phenomena linked to auxiliary hypotheses.

Main Results:

  • Auxiliary hypotheses act as linking assumptions between beliefs and data.
  • They function as a 'protective belt,' absorbing disconfirmation.
  • This rational mechanism explains belief persistence without solely relying on heuristics or motivated reasoning.

Conclusions:

  • Auxiliary hypotheses offer a rational explanation for belief robustness.
  • Their role extends from theoretical philosophy to practical cognitive processes.
  • Understanding these hypotheses is crucial for explaining belief persistence and cognitive biases.