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- Challenges with securing peer reviewers may not be linked to a \u201cshrinking reviewer pool\u201d but underutilisation of the wider global pool.<\/li>\n
- New approaches, such as developing fit-for-purpose search tools, engaging junior experts, and offering viable compensation, may help journals source new peer reviewers.<\/li>\n<\/ul>\n
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<\/p>\nPeer review is key to scientific integrity, so why is it becoming increasingly difficult for journals to secure peer reviewers? This topic was explored in a recent Springer Nature article<\/a> authored by Arunas Radzvilavicius. The huge increase in peer review requests through the publication boom of the last 20 years has made it harder for journals to match peer reviewers. But does this reflect a shrinking reviewer pool?<\/p>\n
In fact, the number of potential reviewers is growing at a faster rate than publications, according to Radzvilavicius. This suggests the \u2018reviewer shortage\u2019 is due to limitations in the methods for matching reviewers. Radzvilavicius describes barriers to securing peer reviewers:<\/p>\n
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- repeat invitations to the same individuals<\/li>\n
- high reviewer workloads<\/li>\n
- distrust of commercial publishers<\/li>\n
- lack of viable incentives<\/a>.<\/li>\n<\/ul>\n
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\u201cJournals should t<\/em>ap into the global reviewer pool to address the \u2018reviewer shortage\u2019.\u201d<\/em><\/p>\n<\/blockquote>\n
Alternative approaches to finding reviewers<\/strong><\/p>\n
Radzvilavicius emphasises journals should tap into the global reviewer pool to address the \u2018reviewer shortage\u2019. Journals could:<\/p>\n
- \n
- Substitute Google Scholar for <\/strong>more advanced<\/strong><\/a>, impartial peer review tools.<\/strong> Radzvilavicius describes Google Scholar as a go-to method of sourcing reviewers, but its algorithms are unclear and prone to bias<\/a>. Fit-for-purpose tools should be developed with global coverage, regular updates, automated invitation\/acceptance rate tracking, and filters to avoid over-used reviewers.<\/li>\n
- Utilise AI<\/strong><\/a>.<\/strong> Automating time-intensive tasks, such as verifying statistics and ethics statements, through large language models<\/a> would significantly reduce reviewers\u2019 workloads.<\/li>\n
- Engage junior expert reviewers. <\/strong>Highlight the opportunities for career progression and acknowledgement that peer review offers, and provide workshops and networking events.<\/li>\n
- Introduce financial compensation. <\/strong>To address concerns that incentivising peer review may impact quality, Radzvilavicius argues that the opposite may be true: \u201cpaying for the service allows you to demand a high-quality product\u201d. \u00a0<\/strong><\/li>\n<\/ul>\n
Radzvilavicius emphasises that there are \u201cplenty of reviewers worldwide\u201d \u2013 we just need better ways of finding them. Changing the approach could offer broad benefits, accelerating quality peer review.<\/p>\n
\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014<\/p>\n
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<\/p>\n - Utilise AI<\/strong><\/a>.<\/strong> Automating time-intensive tasks, such as verifying statistics and ethics statements, through large language models<\/a> would significantly reduce reviewers\u2019 workloads.<\/li>\n
- Substitute Google Scholar for <\/strong>more advanced<\/strong><\/a>, impartial peer review tools.<\/strong> Radzvilavicius describes Google Scholar as a go-to method of sourcing reviewers, but its algorithms are unclear and prone to bias<\/a>. Fit-for-purpose tools should be developed with global coverage, regular updates, automated invitation\/acceptance rate tracking, and filters to avoid over-used reviewers.<\/li>\n