Open access, generative artificial intelligence, and the criminology evidence base

Open access (OA) and generative artificial intelligence (genAI) shape how researchers, practitioners, and policymakers discover and synthesize criminological knowledge. We examined how deep-research tools from three popular genAI platforms handle criminology literature reviews. The systems vary considerably in quality: some produce plausible reports with unreliable citations, while others generate structured reviews drawing predominantly on OA and other free-to-read full-text articles and reports. The findings reveal that genAI is making OA outputs central to criminology’s evidence base. Free materials are easier for both humans and machines to discover, scrutinize, and integrate into policy and practice. Paywalled research is more likely to be ignored. The takeaway is clear: making work OA is more essential than ever for influencing criminology’s future.

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Publication Details

Published
2026-02-03
DOI
https://doi.org/10.21428/7b6d533a.085137cd
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Open access, generative artificial intelligence, and the criminology evidence base

Andrew Palmer Wheeler, Scott Jacques, Joshua Gerstenfeld
Computational and Text Analysis Methods
article

Open access, generative artificial intelligence, and the criminology evidence base

Andrew Palmer Wheeler, Scott Jacques, Joshua Gerstenfeld
article en

Abstract

Open access (OA) and generative artificial intelligence (genAI) shape how researchers, practitioners, and policymakers discover and synthesize criminological knowledge. We examined how deep-research tools from three popular genAI platforms handle criminology literature reviews. The systems vary considerably in quality: some produce plausible reports with unreliable citations, while others generate structured reviews drawing predominantly on OA and other free-to-read full-text articles and reports. The findings reveal that genAI is making OA outputs central to criminology’s evidence base. Free materials are easier for both humans and machines to discover, scrutinize, and integrate into policy and practice. Paywalled research is more likely to be ignored. The takeaway is clear: making work OA is more essential than ever for influencing criminology’s future.

Peace, Justice and strong institutions
Openalex Percentile: Top 78%
Computational and Text Analysis Methods
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