File:Goodfaith miscalibration pred newcomers and anons.png

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Summary

Description
English: ORES is a machine learning system for classifying edits to Wikipedia according to whether they are damaging or goodfaith. This plot shows, for the 25 Wikis on which ORES goodfaith models are deployed, and when the prediction threshold is chosen to maximize overall accuracy, that the model tends to underestimate the incidence of goodfaith edits. We see evidence of systemic bias against such editors in the sense that the models tend to underestimate the probability that their edits are made in good-faith even more than other editors.
Date
Source Own work
Author Groceryheist

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Captions

This plot shows the difference between the average prediction by the model and the average true label for the ORES goodfaith models.

Items portrayed in this file

depicts

inception

23 April 2019

File history

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Date/TimeThumbnailDimensionsUserComment
current16:48, 2 May 2019Thumbnail for version as of 16:48, 2 May 20191,142 × 703 (49 KB)GroceryheistImprove title and axes labels.
22:19, 25 April 2019Thumbnail for version as of 22:19, 25 April 20191,142 × 679 (42 KB)GroceryheistChange axis label.
18:51, 24 April 2019Thumbnail for version as of 18:51, 24 April 20191,142 × 679 (43 KB)Groceryheistshow confidence intervals around points.
05:55, 24 April 2019Thumbnail for version as of 05:55, 24 April 20191,142 × 679 (29 KB)GroceryheistUser created page with UploadWizard

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