The extent and drivers of gender imbalance in neuroscience reference lists
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Abstract (arXiv)
Like many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances within the field. While much of the conversation has centered around publishing and conference participation, recent research in other fields has called attention to the prevalence of gender bias in citation practices. Because of the downstream effects that citations can have on visibility and career advancement, understanding and eliminating gender bias in citation practices is vital for addressing inequity in a scientific community. In this study, we sought to determine whether there is evidence of gender bias in the citation practices of neuroscientists. Using data from five top neuroscience journals, we find that reference lists tend to include more papers with men as first and last author than would be expected if gender were not a factor in referencing. Importantly, we show that this overcitation of men and undercitation of women is driven largely by the citation practices of men, and is increasing over time as the field becomes more diverse. We develop a co-authorship network to assess homophily in researchers' social networks, and we find that men tend to overcite men even when their social networks are representative. We discuss possible mechanisms and consider how individual researchers might address these findings in their own practices.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jan 2020.
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Citing papers per year: 2021: 1; 2022: 6; 2023: 3; 2024: 2; 2025: 0; 2026: 1.
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- 2021NeuroGen: activation optimized image synthesis for discovery neurosciencecited by 22
- 2022Personalized visual encoding model construction with small datacited by 12
- 2023Information decomposition in complex systems via machine learningcited by 9
- 2022Interpretability with full complexity by constraining feature informationcited by 7
- 2022Nonbacktracking spectral clustering of nonuniform hypergraphscited by 4
- 2023Machine-learning optimized measurements of chaotic dynamical systems via the information bottleneckcited by 3
- 2022Nothing makes sense in deep learning, except in the light of evolutioncited by 2
- 2023Gender inference: can chatGPT outperform common commercial tools?cited by 2
- 2022Causal foundations of bias, disparity and fairnesscited by 0
- 2022Evaluating Temporal Patterns in Applied Infant Affect Recognitioncited by 0
- 2024For the Misgendered Chinese in Gender Bias Research: Multi-Task Learning with Knowledge Distillation for Pinyin Name-Gender Predictioncited by 0
- 2024Surveying the space of descriptions of a composite system with machine learningcited by 0
- 2026War in the Abstract: The Rise and Consequences of Militarized Language in Scientific Communication22 Jun 2026
- 2024Surveying the space of descriptions of a composite system with machine learning27 Nov 2024
- 2024For the Misgendered Chinese in Gender Bias Research: Multi-Task Learning with Knowledge Distillation for Pinyin Name-Gender Prediction10 May 2024
- 2023Gender inference: can chatGPT outperform common commercial tools?24 Nov 2023
- 2023Machine-learning optimized measurements of chaotic dynamical systems via the information bottleneck8 Nov 2023
- 2023Information decomposition in complex systems via machine learning10 Jul 2023
- 2022Interpretability with full complexity by constraining feature information30 Nov 2022
- 2022Evaluating Temporal Patterns in Applied Infant Affect Recognition7 Sep 2022
- 2022Causal foundations of bias, disparity and fairness27 Jul 2022
- 2022Nothing makes sense in deep learning, except in the light of evolution20 May 2022
- 2022Nonbacktracking spectral clustering of nonuniform hypergraphs27 Apr 2022
- 2022Personalized visual encoding model construction with small data4 Feb 2022
1 more
- 2021NeuroGen: activation optimized image synthesis for discovery neurosciencecited by 22
- 2022Personalized visual encoding model construction with small datacited by 12
- 2023Information decomposition in complex systems via machine learningcited by 9
- 2022Interpretability with full complexity by constraining feature informationcited by 7
- 2022Nonbacktracking spectral clustering of nonuniform hypergraphscited by 4
- 2023Machine-learning optimized measurements of chaotic dynamical systems via the information bottleneckcited by 3
- 2022Nothing makes sense in deep learning, except in the light of evolutioncited by 2
- 2023Gender inference: can chatGPT outperform common commercial tools?cited by 2
- 2022Causal foundations of bias, disparity and fairnesscited by 0
- 2022Evaluating Temporal Patterns in Applied Infant Affect Recognitioncited by 0
- 2024Surveying the space of descriptions of a composite system with machine learningcited by 0
- 2026War in the Abstract: The Rise and Consequences of Militarized Language in Scientific Communicationcited by 0
- 2026War in the Abstract: The Rise and Consequences of Militarized Language in Scientific Communication22 Jun 2026
- 2024Surveying the space of descriptions of a composite system with machine learning27 Nov 2024
- 2023Gender inference: can chatGPT outperform common commercial tools?24 Nov 2023
- 2023Machine-learning optimized measurements of chaotic dynamical systems via the information bottleneck8 Nov 2023
- 2023Information decomposition in complex systems via machine learning10 Jul 2023
- 2022Interpretability with full complexity by constraining feature information30 Nov 2022
- 2022Evaluating Temporal Patterns in Applied Infant Affect Recognition7 Sep 2022
- 2022Causal foundations of bias, disparity and fairness27 Jul 2022
- 2022Nothing makes sense in deep learning, except in the light of evolution20 May 2022
- 2022Nonbacktracking spectral clustering of nonuniform hypergraphs27 Apr 2022
- 2022Personalized visual encoding model construction with small data4 Feb 2022
- 2021NeuroGen: activation optimized image synthesis for discovery neuroscience15 May 2021