* wary of self assessing
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Replying to @Ben_C_J @IrisVanRooij and
I see what you are all getting at but there is a real other issue here that I skimmed and didn't notice.
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For example, I tried to replicate two models during my PhD and one doesn't replicate. The other has a mistake in a graph which is very cute as I think it was a bug in their original code and they state "we expected X but we got this graph instead", the correct graph shows X.
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And yes,
@ReScienceEds try very hard to tackle this issue by publishing only replications of computational models (not just cognitive ones though).1 reply 0 retweets 4 likes -
I have discussed this issue in a few different places. Here with
@NPRougier Guest, O. & Rougier, N. P. (2016). Dialogue: What is Computational Reproducibility?. IEEE CIS Newsletter on Cognitive and Developmental Systems. 13 (2). http://oliviaguest.com/doc/guest_rougier_2016.pdf …2 replies 2 retweets 3 likes -
This blog post that
@chbergma invited me to write (thank you!): http://bootphon.blogspot.co.uk/2015/10/replication-in-computational-cognitive.html …1 reply 1 retweet 4 likes -
This paper: Implementations are not specifications: Specification, replication and experimentation in computational cognitive modeling https://doi.org/10.1016/j.cogsys.2013.05.001 …
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So there are more than a single issue here but I have been discussing this usually on my own and often without any support from others since the academic year of 2009/2010.
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:( It's sad people don't see the importance of the points you've brought up. It's fascinating to see another field facing nearly the same issues as machine learning research and suggesting similar trajectories through them.
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Yup! Not only similar issues, but I think the "root" is the same and the crossover of people/ideas from the two areas is not a coincidence!
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I wanted to say something like, really subfields of the same field distinguished by emphasis placed on biological plausibility but thought that sounded to much like the kind of thing physicists say :p
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