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What Underpins Model Credibility? Three Philosophical Perspectives

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Manage episode 482276486 series 3608409
Content provided by UK CEiRSI | InSilicoUK. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UK CEiRSI | InSilicoUK or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

How do philosophers of science think about model evaluation? Dive deep into the crucial process of model evaluation, a fundamental step in digital science that determines the effectiveness and precision of computational models.

This episode explores three primary perspectives on model quality: the mirror view, relevant similarity, and fitness for purpose. Learn about the complexities and challenges involved in evaluating models, from data limitations to the intricate balance between accuracy and usability.

Whether you're a researcher, regulator, or a curious listener, discover how these cutting-edge methodologies are reshaping healthcare, improving safety, efficiency, and equitability, one simulated trial at a time. Join us as we delve into the philosophy behind model evaluation and unveil the real-world impact of digital innovation.
Parker WS. Model Evaluation: An Adequacy-for-Purpose View. Philos Sci. 2020;87(3):457-477.

Bokulich A, Parker W. Data models, representation and adequacy-for-purpose. Eur J Philos Sci. 2021;11(31).

  continue reading

41 episodes

Artwork
iconShare
 
Manage episode 482276486 series 3608409
Content provided by UK CEiRSI | InSilicoUK. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UK CEiRSI | InSilicoUK or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

How do philosophers of science think about model evaluation? Dive deep into the crucial process of model evaluation, a fundamental step in digital science that determines the effectiveness and precision of computational models.

This episode explores three primary perspectives on model quality: the mirror view, relevant similarity, and fitness for purpose. Learn about the complexities and challenges involved in evaluating models, from data limitations to the intricate balance between accuracy and usability.

Whether you're a researcher, regulator, or a curious listener, discover how these cutting-edge methodologies are reshaping healthcare, improving safety, efficiency, and equitability, one simulated trial at a time. Join us as we delve into the philosophy behind model evaluation and unveil the real-world impact of digital innovation.
Parker WS. Model Evaluation: An Adequacy-for-Purpose View. Philos Sci. 2020;87(3):457-477.

Bokulich A, Parker W. Data models, representation and adequacy-for-purpose. Eur J Philos Sci. 2021;11(31).

  continue reading

41 episodes

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