Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Does response scaling cause the generalized context model to mimic a prototype model?

Jay I Myung1, Mark A Pitt, Daniel J Navarro

  • 1Department of Psychology, Ohio State University, Columbus 43210, USA. myung.1@osu.edu

Psychonomic Bulletin & Review
|January 31, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Rapid and reliable computational markers of decision-making for predicting daily smoking behavior and smoking cessation treatment outcomes.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same author

A tutorial on using generative models to advance psychological science: Lessons from the reliability paradox.

Psychological methods·2025
Same author

Correction: Assessing the distortions introduced when calculating d': A simulation approach.

Behavior research methods·2025
Same author

Assessing the distortions introduced when calculating d': A simulation approach.

Behavior research methods·2024
Same author

Uncertainty limits the use of power analysis.

Journal of experimental psychology. General·2024
Same author

Implementation of an online spacing flanker task and evaluation of its test-retest reliability using measures of inhibitory control and the distribution of spatial attention.

Behavior research methods·2024
Same journal

Mind wandering during first- and foreign-language reading.

Psychonomic bulletin & review·2026
Same journal

Lexical word processing is unaffected by rapid invisible frequency tagging in reading: Evidence from eye movements.

Psychonomic bulletin & review·2026
Same journal

Anxiety modulates voluntary attentional orienting to emotional gaze cues: Eye movements for pro- and anti-saccades.

Psychonomic bulletin & review·2026
Same journal

Faster key-press responses to front vowels than back vowels when matching heard vowels with represented vowels.

Psychonomic bulletin & review·2026
Same journal

Testing the interleaving effect without response bias: A forced-choice reevaluation of Kornell and Bjork (2008).

Psychonomic bulletin & review·2026
Same journal

The impact of social interaction on abstract concepts.

Psychonomic bulletin & review·2026
See all related articles

The generalized context model (GCM) complexity is evaluated, finding the response scaling parameter does not necessarily lead to mimicry of prototype models. Statistical methods enhance model discrimination.

Area of Science:

  • Cognitive Science
  • Computational Psychology
  • Mathematical Psychology

Background:

  • The Generalized Context Model (GCM) is an exemplar-based theory of categorization.
  • A criticism suggests the GCM's response scaling parameter (y) increases complexity and allows mimicry of prototype models.
  • The debate centers on whether the GCM's flexibility is a feature or a flaw.

Purpose of the Study:

  • To evaluate the criticism regarding the GCM's response scaling parameter (y).
  • To assess the complexity of the GCM with and without the y parameter.
  • To compare the GCM's mimicry of prototype models across different experimental designs.

Main Methods:

  • Complexity estimation of GCM (with and without y) and a prototype model.
  • Model mimicry assessment using two distinct experimental designs (Nosofsky & Zaki, 2002; Smith & Minda, 1998).

Related Experiment Videos

  • Application of statistical model selection methods, such as minimum description length (MDL).

    • Main Results:

    • The parameter y can increase GCM complexity.
    • Increased GCM complexity does not inherently lead to mimicry of prototype models.
    • Statistical model selection methods effectively discriminate between GCM and prototype models, regardless of experimental design.

    Conclusions:

    • The criticism that the GCM's response scaling parameter (y) leads to unnecessary complexity and mimicry is not fully supported.
    • Model selection criteria are crucial for distinguishing between exemplar and prototype models.
    • The GCM remains a distinct and viable model of categorization, even with the inclusion of the y parameter.