# 3124 | ResearchBox


ResearchBox #3124 - 'Harvard’s Gino Report Shows Us How A Dataset Was Altered'


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Data Colada 118


  Study 3A Materials.docx


  


  Data Cleaned & Re-constructed.csv


  


  Data From Colada 112.csv


  


  Data From Harvard Report.csv


  


  Gino et al. (2020) Study 3A Posted Data.csv



  Colada 118 R Code - To Post.R



  Figures in Post 118 (Final).pptx


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BOX INFORMATION

SUPPLEMENTARY FILES FOR
Joseph Simmons, 'Harvard’s Gino Report Shows Us How A Dataset Was Altered', Data Colada
https://datacolada.org/118

LICENSE FOR USE
All content posted to ResearchBox is under a CC By 4.0 License (all use is allowed as long as authorship of the content is attributed). When using content from ResearchBox please cite the original work, and provide a link to the URL for this box (https://researchbox.org/3124).

BOX PUBLIC SINCE
June 19, 2024   

BOX CREATORS
Joseph Simmons (jsimmo@upenn.edu)

ABSTRACT
As you may know, Harvard professor Francesca Gino is suing us for defamation after (1) we alerted Harvard to evidence of fraud in four studies that she co-authored, (2) Harvard investigated and placed her on administrative leave, and (3) we summarized the evidence in four blog posts. As part of their investigation, Harvard wrote a 1,288-page report describing what they found. Because of the lawsuit, that report was made public: .pdf. And because it was made public, we now know what the investigators say was in the "original" dataset for one of the four studies: Study 3A of Gino, Kouchaki, and Casciaro (2020). By simply comparing the Original and Posted versions of the dataset, we can see exactly how the data were altered to produce the published result. In this post, we will show that (1) we correctly deduced how the data were altered and (2) Gino's explanation for the alterations is extremely implausible.

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Dear Reader,

The R Code contains what you need to build the re-constructed dataset from (1) the original data file, (2) the data from the Harvard Report, and (3) the data from Colada 112. So you don't need the "Cleaned and Re-constructed" dataset to run any of the code. The code will create it. I have it here so that people can look at it (or start from it) if they want.



This version: June 11, 2024