The DOI matches its DataCite record.
Where is the evidence: realising the value of grey literature for public policy and practice
Open accessAbstract
The internet has profoundly changed how we produce, use and collect research and information for public policy and practice, with grey literature playing an increasingly important role. The authors argue that grey literature (i.e. material produced and published by organisations without recourse to the commercial or scholarly publishing industry) is a key part of the evidence produced and used for public policy and practice. Through surveys of users, producing organisations and collecting services a detailed picture is provided of the importance and economic value of grey literature. However, finding and accessing policy information is a timeconsuming task made harder by poor production and management of resources and a lack of large-scale collection services able to host and make available relevant, high-quality resources quickly and efficiently. The paper makes recommendations for changes that would maximise the benefits of grey literature in the public interest and seeks feedback from readers to inform the final report of the research project.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“No study, for instance, has tested grey literature and non-English literature, which can constitute a large proportion of the evidence base for some topics (Lawrence et al., 2014).”
From Can large language models replace humans in systematic reviews? Evaluating GPT ‐4's efficacy in screening and extracting data from peer‐reviewed and grey literature in multiple languages (2024) · cites this paper as Lawrence et al., 2014
Citations
Cited by
Sorted by citations
Garousi, V., Felderer, M., & Mäntylä, M. V. (2019) · Information and Software Technology · doi:10.1016/j.infsof.2018.09.006 · Cited by 831
Khraisha, Q., Put, S., Kappenberg, J., Warraitch, A., & Hadfield, K. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1715 · Cited by 269
Khraisha, Q., Put, S., Kappenberg, J., Warraitch, A., & Hadfield, K. (2023) · arXiv · doi:10.48550/arxiv.2310.17526 · Cited by 268
Cassell, K., Ologunowa, A., Rastegar-Mojarad, M., Chun, B., Huang, Y.-L., Wang, D., & Cossrow, N. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1662202 · Cited by 6
Metadata
- Authors
- Lawrence, A., Houghton, J., & Thomas, J.
- Venue
- Swinburne Institute for Social Research
- Publisher
- Swinburne Institute for Social Research
- Published
- 2014
- OpenAlex
- W2214143284
- Cited by
- 31
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 5 · 2021: 2 · 2020: 1 · 2019: 1 · 2018: 5 · 2017: 3 · 2016: 3 · 2015: 3
- FWCI
- 6.23
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc
- Locations
- Swinburne figshare (Swinburne University of Technology) (acceptedVersion, cc-by-nc)
- ACEReSearch Repository (Australian Council for Educational Research) (submittedVersion, cc-by)
- RMIT Research Repository (RMIT University Library) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by-nc)
- Swinburne figshare (Swinburne University of Technology)
- Funders
- University of Warwick
- National Library of Australia
- Swinburne University of Technology
- Victoria University
- Topics
- Social Sciences › Library and Information Sciences › Optics and Image Analysis
- Social Sciences › Library and Information Sciences › Library Science and Information
- Social Sciences › Library and Information Sciences › Information Science and Libraries
- Keywords
- grey literature, public policy, evidence-based policy, policy information, access to information, collection services, information management
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Where is the evidence: realising the value of grey literature for public policy and practice. https://app.cochat.ai/papers/10.4225/50/5580b1e02daf9
- The paper
- Lawrence, A., Houghton, J., & Thomas, J. (2014). Where is the evidence: realising the value of grey literature for public policy and practice. Swinburne Institute for Social Research. https://doi.org/10.4225/50/5580b1e02daf9
