QRPs in Humanities Research

Questionable research practices (QRPs) lie in the gray area between responsible research conduct (best practices) and research misconduct. These videos briefly present QRPs that arise in four areas of quantitative Humanities research:

1. Funding
2. Design and Data Collection
3. Data Analysis and Interpretation
4. Write-up and Dissemination

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About us: We are a research team examining questionable research practices (QRPs) in quantitative humanities research. The project is co-funded by the Swedish Research Council, the Bank of Sweden Tercentenary Foundation, and the Royal Swedish Academy of Letters, History and Antiquities. Visit our webpage for more information about questionable research practices in humanities research: https://sites.google.com/view/qrp-humanities?pli=1

Write-Up/Dissemination, QRP #17: Inappropriately attributing author roles when listed in publication
Write-Up/Dissemination, QRP #17: Inappropriately attributing author roles when listed in publication
Write-Up/Dissemination, QRP #10: Presenting misleading figures of data
Write-Up/Dissemination, QRP #10: Presenting misleading figures of data
Data Analysis/Interpretation, QRP #10: Handling missing data
Data Analysis/Interpretation, QRP #10: Handling missing data
Write-up/Dissemination, QRP #4: The file drawer issue
Write-up/Dissemination, QRP #4: The file drawer issue
Write-up/Dissemination, QRP#18: Inappropriate ordering of authors
Write-up/Dissemination, QRP#18: Inappropriate ordering of authors
Write-up/Dissemination, QRP #14: Employing excessive self-citation
Write-up/Dissemination, QRP #14: Employing excessive self-citation
Write-up/Dissemination: QRP#3: Not providing sufficient description of the data and the results
Write-up/Dissemination: QRP#3: Not providing sufficient description of the data and the results
Data Analysis/Interpretation, QRP#8: p-hacking
Data Analysis/Interpretation, QRP#8: p-hacking
Data Analysis/Interpretation, QRP #7: Choosing a method of analysis to get a favorable outcome
Data Analysis/Interpretation, QRP #7: Choosing a method of analysis to get a favorable outcome
Write-up/Dissemination, QRP#5: Employing selective reporting of results/instruments
Write-up/Dissemination, QRP#5: Employing selective reporting of results/instruments
Write-up/Dissemination, QRP#9: Not attempting to publish results in a timely manner
Write-up/Dissemination, QRP#9: Not attempting to publish results in a timely manner
Write-up/Dissemination, QRP#2: Inadequate description of the data analyses or other procedures
Write-up/Dissemination, QRP#2: Inadequate description of the data analyses or other procedures
Data Analysis/Interpretation, QRP #3: Not being transparent about steps taken in data cleaning
Data Analysis/Interpretation, QRP #3: Not being transparent about steps taken in data cleaning
Data Analysis/Interpretation, QRP #2: Unjustified methods of handling outliers
Data Analysis/Interpretation, QRP #2: Unjustified methods of handling outliers
Write-up/Dissemination, QRP #15: Intentionally omitting relevant work
Write-up/Dissemination, QRP #15: Intentionally omitting relevant work
Data Analysis/Interpretation, QRP #14: Interpreting statistical results inappropriately
Data Analysis/Interpretation, QRP #14: Interpreting statistical results inappropriately
Data Analysis/Interpretation, QRP#13: Using the incorrect statistical methods
Data Analysis/Interpretation, QRP#13: Using the incorrect statistical methods
Data Analysis/Interpretation, QRP #6: Cherry-picking data to analyze
Data Analysis/Interpretation, QRP #6: Cherry-picking data to analyze
Data Analysis/Interpretation, QRP #1: Removing whole items purposefully to obtain a favorable result
Data Analysis/Interpretation, QRP #1: Removing whole items purposefully to obtain a favorable result
Design/Data Collection, QRP #2: Sacrificing validity for a more convenient design or instrument
Design/Data Collection, QRP #2: Sacrificing validity for a more convenient design or instrument
Data Analysis/Interpretation, QRP #5: HARKing (hypothesizing after results are known)
Data Analysis/Interpretation, QRP #5: HARKing (hypothesizing after results are known)
Data Analysis/Interpretation, QRP #11: Categorizing continuous variables
Data Analysis/Interpretation, QRP #11: Categorizing continuous variables
Data Analysis/Interpretation, QRP #9: Alternate explanations of data
Data Analysis/Interpretation, QRP #9: Alternate explanations of data
Data Analysis/Interpretation, QRP #12: Using too many statistical tests without correction
Data Analysis/Interpretation, QRP #12: Using too many statistical tests without correction
Write-up/Dissemination, QRP #1: Failing to cite relevant work
Write-up/Dissemination, QRP #1: Failing to cite relevant work
Write-up/Dissemination, QRP #16: Inappropriately including or excluding authors
Write-up/Dissemination, QRP #16: Inappropriately including or excluding authors
Design/Data Collection, QRP #7: Not reporting the effect of decisions about study design on outcomes
Design/Data Collection, QRP #7: Not reporting the effect of decisions about study design on outcomes
Write-up/Dissemination, QRP #21: Lifting short phrases
Write-up/Dissemination, QRP #21: Lifting short phrases
Write-up/Dissemination, QRP #20: Exaggerating the importance of findings in order to get published
Write-up/Dissemination, QRP #20: Exaggerating the importance of findings in order to get published
Write-up/Dissemination, QRP #13: Presenting the same presentation at multiple conferences
Write-up/Dissemination, QRP #13: Presenting the same presentation at multiple conferences