Leaders’ gender and the fight against COVID-19: investigation, replication, and a possible explanation

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Abstract

Objectives

To investigate the alleged relationship between leaders’ gender and COVID-19 related cases and deaths in different countries across the globe.

Study design

The relationship between leaders’ gender and percent of women in parliament to COVID-19 cases and death per million was investigated in three time points (10 months) across 180 countries, controlling for possible covariates.

Methods

Three different types of analyses were run: (1) Six basic t-tests; (2) Two repeated-measure ANOVA tests analyzing change over time; (3) Six stepwise regression analyses for both leaders’ gender and the percentage of women in parliament.

Results

Our findings suggest that, contrary to some research and popular media headlines, and in-line with recent academic research, leadership gender is not a significant factor in explaining the variation between countries in the fight against the COVID-19 pandemic.

Conclusions

We suggest that this alleged relationship may stem from an illusory correlation. We argue that the uncertainty, stress, and anxiety that prevail in these times of global pandemic may be the breeding ground for judgmental biases of this sort.

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  1. SciScore for 10.1101/2021.10.12.21264903: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableAltogether, we ran three different types of analyses to assess the relationship between leaders’ gender and COVID-19 cases and deaths: (1) Six basic t-tests - comparing cases and deaths between countries led by women and countries led by men in each of the three time points (Table 1); (2) Two repeated-measure ANOVA tests – analyzing the change in COVID-19 cases and deaths by leaders’ gender through time (Table 1); (3) Six stepwise regression analyses - examining the association between leaders gender and the percentage of women in parliament with the number of cases and deaths for each of the three time points (See supplementary materials for the complete analyses).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.