Research Brief: June 2026
- Darwin
- Jun 29
- 5 min read
It's been a quieter month for brand-new studies, but the half-dozen I've gathered are well worth your time - there's work on AI and body-worn cameras, the fairness of camera versus officer enforcement, stop and search, why people do (and don't) report crime, the shifting geography of vehicle theft, and domestic abuse within the police workforce itself. As always, if you spot something I've missed, let me know and I'll add it to the next edition.
TL;DR?
Artificial intelligence in police research: a preliminary examination of feasibility and replication
An AI tool broadly reproduced a de-escalation training trial's findings from body-worn camera footage, but its hard-to-inspect design warrants caution.
Camera or cop: the procedural justice of AI-camera and officer enforcement of mobile phone offending - Drivers saw enforcement by an officer as fairer than an AI detection camera, even for the same offence and outcome.
Procedural justice in police stop and search encounters: crime contexts and police versus public assessments - Police and the public can judge the fairness of the very same recorded stop-and-search quite differently.
The map and the territory: cognitive thresholds in crime reporting - Willingness to report crime varies systematically by demographics, so recorded crime is a partial, socially filtered map of harm.
Measuring macro and micro geospatial changes in New York City's motor vehicle thefts - A new spatial method tracks how the geography of vehicle theft shifted during COVID-19 restrictions.
Domestic abuse victimisation in a police workforce: victim experience and the institutional response - A qualitative look at the role conflict facing officers and staff who are themselves victims of domestic abuse (preprint).
Artificial intelligence in police research: a preliminary examination of feasibility and replication
Authors: McLean, Rojek & Nix
Study design: Replication study using AI to re-analyse body-worn camera footage from a randomised controlled trial
Setting: United States
Summary: Researchers tested whether a commercial AI tool (TrustStat) could reproduce findings from a randomised trial of police de-escalation training that originally relied on painstaking human coding of body-worn camera footage. The AI-generated measures reached the same overall conclusion as the human analysis - trained officers communicated more calmly - though several AI and human measures did not align. The authors urge caution given the tool's proprietary, hard-to-inspect design.
You'll be interested if: you're weighing whether AI tools can speed up the analysis of body-worn camera footage, or you commission research and evaluation and want to understand both the promise and the limits of off-the-shelf AI for measuring officer behaviour.
Camera or cop: the procedural justice of AI-camera and officer enforcement of mobile phone offending
Authors: Truelove, Anderson, Bates & Oviedo-Trespalacios
Study design: Mixed methods (interviews with 26 officers and a survey of 292 drivers)
Setting: Australia
Summary: Combining interviews with 26 traffic officers and a survey of 292 drivers, this study compared how people perceive the fairness of mobile-phone-offence enforcement by police officers versus AI detection cameras. Drivers rated officer enforcement as fairer and felt more listened to, respected and treated politely, with greater confidence in the decision. Perceptions of 'voice' and trustworthy motives did not differ between the two methods.
You'll be interested if: your force is expanding automated enforcement - speed, mobile-phone or other detection cameras — and you want to understand how removing the human interaction may affect public perceptions of fairness, trust and legitimacy.
Procedural justice in police stop and search encounters: crime contexts and police versus public assessments
Authors: Tansill & Tankebe
Study design: Observational study coding 140 stop-and-search encounters on body-worn video
Setting: England
Summary: Using systematic analysis of 140 stop-and-search encounters captured on body-worn video in an English force, this study examined the quality of police behaviour — judged against procedural justice principles - and how it varied between higher-crime and lower-crime areas. It also offers a rare direct comparison of how police supervisors and members of the public rated the same recorded encounters, surfacing differences in how each group judges identical behaviour.
You'll be interested if: you lead or scrutinise stop and search, run a scrutiny panel, or supervise officers — the study speaks directly to how encounter quality is assessed and how police and public judgements of the same interaction can diverge.
The map and the territory: cognitive thresholds in crime reporting
Authors: Stubbs
Study design: Cross-sectional survey (n=1,948) with clustering analysis
Setting: England and Wales
Summary: A survey of 1,948 adults in England and Wales asked how likely they would be to report crimes of escalating severity. Using clustering, the study identified three distinct 'reporting profiles'. Willingness to report varied with income, education and employment, and lower-harm offences were interpreted far more unevenly than serious ones - particularly among more disadvantaged groups - suggesting police-recorded crime is a socially filtered, partial map of actual harm.
You'll be interested if: you work with crime data, demand analysis or community confidence, and want a reminder that recorded crime reflects who chooses to report as much as what happens, with equity implications for how lower-harm offences are counted.
Measuring macro and micro geospatial changes in New York City's motor vehicle thefts
Authors: Cubitt, Connealy & Sherman
Study design: Geospatial analysis using a natural experiment (before and after a policy change)
Setting: United States
Summary: This study introduces a spatial analysis method - 'Distance of Distances' - for detecting clusters of crime, and tests whether it can track changes in where crime happens after a major disruption. Using New York City's COVID-19 'shelter in place' period, the authors examined shifts in motor vehicle theft both citywide and around acute-care hospitals, demonstrating the method's ability to capture both macro and micro geographic change.
You'll be interested if: you work in crime analysis, hot-spot targeting or performance measurement and want a new technique for spotting how the geography of crime shifts after a policy change or major event.
Domestic abuse victimisation in a police workforce: victim experience and the institutional response
Authors: O'Leary, Brennan & Couto
Study design: Qualitative study (analysis of open-ended survey responses)
Setting: England
Summary: This study examines the experiences of domestic abuse victim-survivors who work in policing - an under-researched group facing a clear role conflict between being victims and being part of the institution that responds to abuse. Through qualitative analysis of open-ended survey responses from staff in an English force, it explores how victims experienced the abuse and their force's institutional response, and the private and professional harms that can follow.
Note: this is a preprint and has not yet been peer reviewed.
You'll be interested if: you have responsibility for workforce wellbeing, professional standards, HR or the VAWG agenda, and want to understand how officers and staff who are themselves victims of domestic abuse experience reporting and support within their own organisation.