Including non-academics in evaluation

Including non-academics in evaluation broadens perspectives by integrating stakeholders from industry, policy, and society. It enhances relevance, transparency, and societal impact, mitigates disciplinary bias, and supports responsible research assessment aligned with real-world needs and principles of openness, inclusiveness, and accountability.
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Challenge - Process
Challenge - Inclusivity
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Experiments in Assessment WG

Last updated

March 10, 2026

WarningObjectives and potential outcome

Research domains

This is especially relevant for funding evaluation, especially when assessing impacts, but it could also be relevant in a variety of domains and settings.

Context and considerations

Challenges and mitigations

Evaluating success

Relevant resources and literature

This section includes resources, literature, and reports relevant to this specific experimental idea.

Junwen Luo, Lai Ma, Kalpana Shankar, Does the inclusion of non-academic reviewers make any difference for grant impact panels?, Science and Public Policy, Volume 48, Issue 6, December 2021, Pages 763–775, https://doi.org/10.1093/scipol/scab046.

Junwen Luo (2021, 25 August), What role should non-academics have in evaluating the potential impact of new research projects? LSE Impact Blog, Available here.

Baxter S, Clowes M, Muir D, Baird W, Broadway-Parkinson A, Bennett C. (2016) Supporting public involvement in interview and other panels: a systematic review. Health Expect, 20(5). p. 807-817. https://doi.org/10.1111/hex.12491.

A blog post that describes the experience as a public member of a research funding panel: Adam Forristal Golberg (2025, 25 February), A peek inside a research funding panel, Cash for Questions: Research funding, policy and development, https://socialscienceresearchfunding.co.uk/?p=1455.

Templates from funders and institutions

Case examples and literature

Several funders involve members of the public in their review panels, see for example NIHR and Health Research Board Ireland.

Other resources

Comments/lived examples