REVIEW 1 cited by
Perspectives on Machine Learning from Psychology's Reproducibility Crisis
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
In the early 2010s, a crisis of reproducibility rocked the field of psychology. Following a period of reflection, the field has responded with radical reform of its scientific practices. More recently, similar questions about the reproducibility of machine learning research have also come to the fore. In this short paper, we present select ideas from psychology's reformation, translating them into relevance for a machine learning audience.
Forward citations
Cited by 1 Pith paper
-
On the Role of Speech Data in Reducing Toxicity Detection Bias
Group-annotated MuTox reveals that speech-aware inference reduces false-positive bias against group mentions in English and Spanish, while transcript correction barely changes it.
Discussion (0). Continue with ORCID to comment.