An international survey of applied face-matching training courses.

Face matching decisions in applied settings are typically carried out by trained face-matching professionals, known as facial reviewers and facial examiners. Recent research has demonstrated that short professional face-matching training courses are limited in improving face-matching accuracy, however, despite the existence of high-level training guidelines produced by the practitioner community the content, duration and delivery of training for facial reviewers and facial examiners are not widely understood in the academic research community. The current study aimed to address this gap in the scientific literature to better understand how different agencies train facial reviewers and facial examiners, using results collected from an international survey.

The sibling familiarity effect: Is within?person facial variability shared across siblings?

Humans are experts at familiar face recognition, but poor at unfamiliar face recognition. Familiarity is created when a face is encountered across varied conditions, but the way in which a person's appearance varies is identity?specific, so familiarity with one identity does not benefit recognition of other individuals. However, the faces of biological siblings share structural similarities, so we explored whether the benefits of familiarity are shared across siblings.

Digital Detectives: Websleuthing Reduces Eyewitness Identification Accuracy in Police Lineups.

Eyewitnesses to crimes sometimes search for a culprit on social media before viewing a police lineup, but it is not known whether this affects subsequent lineup identification accuracy. The present online study was conducted to address this. Two hundred and eighty-five participants viewed a mock crime video, and after a 15-20 min delay either (i) viewed a mock social media site including the culprit, (ii) viewed a mock social media site including a lookalike, or (iii) completed a filler task.

Recognising Familiar Faces Out of Context.

Expertise in familiar face recognition has been well-documented in several studies. Here, we examined the role of context using a surprise lecturer recognition test. Across two experiments, we found few students recognised their lecturer when they were unexpected, but accuracy was higher when the lecturer was preceded by a prompt.

Entitlement to Tell on Police Facebook Sites.

Despite the increased use of social media by the police, little qualitative exploration has been carried out regarding how online spaces such as Facebook might be important sites for Police Force identity. This study qualitatively analyzes a popular story told on the official Facebook site of a rural police force. It analyzes the story which is co-created by both the police and the public, and looks at how identity is created for the police through this online activity.

Can Link Analysis Be Applied to Identify Behavioral Patterns in Train Recorder Data?

Objective: A proof-of-concept analysis was conducted to establish whether link analysis could be applied to data from on-train recorders to detect patterns of behavior that could act as leading indicators of potential safety issues.

Background: On-train data recorders capture data about driving behavior on thousands of routine journeys every day and offer a source of untapped data that could be used to offer insights into human behavior.

Method: Data from 17 journeys undertaken by six drivers on the same route over a 16-hr period were analyzed using link analysis, and four key metrics were examined: number of links, network density, diameter, and sociometric status.

Big data and ergonomics methods: A new paradigm for tackling strategic transport safety risks.

Big data collected from On-Train Data Recorders (OTDR) has the potential to address the most important strategic risks currently faced by rail operators and authorities worldwide. These risk issues are increasingly orientated around human performance and have proven resistant to existing approaches. This paper presents a number of proof of concept demonstrations to show that long standing ergonomics methods can be driven from big data, and succeed in providing insight into human performance in a novel way.