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Open Science and its Enemies. Part I: The p-circlers

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Manage episode 419148807 series 2916663
Content provided by Dr Nick Holmes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dr Nick Holmes 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://player.fm/legal.

There's no brain news this month, but i take this unique opportunity to provide the first of my three part critique of - some parts of - the Open Science movement. This episode focusses on p-circling & reverse p-hacking. These two pejorative terms describe situations where scientists who *don't like* a particular reported effect, then decide to search for things in the paper which can 'un-explain' it. The reverse p-hacker turns a significant effect into a non-significant, or un-interesting one. These reverse p-hackers selectively adjust their version of data analysis (or interpretation) to *remove* significant p-values.

it's the same thing as p-hacking. but backwards. & equally wrong.

  continue reading

44 episodes

Artwork
iconShare
 
Manage episode 419148807 series 2916663
Content provided by Dr Nick Holmes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dr Nick Holmes 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://player.fm/legal.

There's no brain news this month, but i take this unique opportunity to provide the first of my three part critique of - some parts of - the Open Science movement. This episode focusses on p-circling & reverse p-hacking. These two pejorative terms describe situations where scientists who *don't like* a particular reported effect, then decide to search for things in the paper which can 'un-explain' it. The reverse p-hacker turns a significant effect into a non-significant, or un-interesting one. These reverse p-hackers selectively adjust their version of data analysis (or interpretation) to *remove* significant p-values.

it's the same thing as p-hacking. but backwards. & equally wrong.

  continue reading

44 episodes

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