Despite sustained investment in gender-equity initiatives, hierarchies of authority, legitimacy and reward remain entrenched in higher education. This paper synthesises two staff surveys conducted in Athena Swan-accredited institutions in the United Kingdom and SAGE Athena Swan-accredited institutions in Australia. We develop a processual account of how gendered advantage is accumulated and defended within institutions recognised for equity progress. Across the studies, encouragement, sponsorship, workload protection and recognition operated as informal judgements of deservingness that shaped who entered formal evaluation with credibility and institutional momentum. Resistance became more visible when equity initiatives rendered these arrangements contestable, appearing through appeals to merit, reverse-discrimination claims and institutional withdrawal. We theorise these mechanisms as operating at different organisational speeds: deservingness is slow, cumulative and ordinarily obscured, whereas backlash is faster, reactive and more visible. Backlash is therefore treated as diagnostic evidence of the status, resources and authority being defended. This framework explains how accreditation can generate substantial activity while leaving informal distributions of legitimacy comparatively intact.

Systems thinking models and methods are currently popular in road safety research. Though the philosophy is beginning to gain traction in road safety, work is required to fully translate and embed its core principles and approaches in practice. A critical element of this involves communicating and demonstrating the core principles of systems theory to road safety practitioners. The aim of this chapter is to present an overview of the systems thinking approach, demonstrate how it has been applied to date in road safety, and outline some critical initial steps to support its implementation in road safety practice. We present a series of case studies focused on road crash analysis and the fatal five causes of road trauma to demonstrate how systems thinking principles and methods can usefully be applied. To close, we discuss the implications for road safety practice by first presenting a set of key principles that road safety stakeholders can adopt to facilitate the translation of systems thinking in road safety practice and second by examining how current road safety strategies could potentially be modified to incorporate core systems thinking principles.

Collisions between trains and road users (drivers, cyclists, motorcyclists and pedestrians) at railway crossings remain a complex safety problem. Safety at railway level crossings is highly reliant on the decisions and actions of road users; therefore, adopting human factors and systems thinking approaches to the design of level crossings is vital. In relation to the physical design of a level crossing, adopting a human factors approach involves taking a user-centred perspective on design and supporting safe user decision-making and behaviour. This chapter provides an overview of human factors considerations and processes that can be used to improve railway level crossing safety, including the consideration of road user tasks while encountering and traversing crossings, design tools such as scenarios to consider user characteristics and motivations, and an overview of human factors risks and potential countermeasures that can address risk at different types of crossings. Overall, it is emphasised that each railway level crossing is unique and should be assessed and designed with relevance to the particular context in which it is situated.

Technology-facilitated intimate partner violence (TFIPV) is increasingly featured in cases of intimate partner violence and intimate partner homicide. There is emerging recognition of the use of technology to abuse and control intimate partners in domestic abuse research and the inherent complexity of TFIPV is evident. As such, a better understanding of the factors that influence TFIPV is necessary. This scoping review aimed to synthesise extant literature on factors known to influence TFIPV. The review included 84 peer-reviewed primary sources that focused on adult intimate relationships (at least 18 years of age), had full-text versions in English, and included individual, situational, environmental, technological, and systemic factors found to increase the likelihood of TFIPV. The influencing factors were extracted and mapped onto a systems-thinking-based framework, Rasmussen's Risk Management Framework. This synthesis identified 28 higher-order themes across the TFIPV system hierarchy. Most of the factors within these themes related to lower levels of the system (e.g. perpetrators, victim-survivors, social environment, device and software capabilities), with limited consideration of broader systemic factors that influence TFIPV. Of the broader systemic factors that were identified, most related to inadequate responses to TFIPV by government, judicial system, technology industry regulators, and police. Future research should consider the use of systems-thinking-based frameworks and methods in understanding and addressing this complex and pervasive problem from a whole-of-system perspective.

Suicide is a leading cause of premature mortality worldwide, making suicide prevention a global public health priority. As more Artificial Intelligence (AI)-based suicide prevention interventions are being developed and implemented, it is important to study acceptance of these AI systems. The present study aimed to investigate the factors that predict acceptance of current and future AI systems for suicide prevention and the perceived risks and benefits of these AI systems. Individuals from the Australian public were invited to participate in an online survey, which included six hypothetical scenarios of current AI systems (Artificial Narrow Intelligence [ANI]) and future advanced AI systems (Artificial General Intelligence [AGI]) for suicide prevention. Participants evaluated these scenarios on five technology acceptance factors (performance expectancy, effort expectancy, social influence, facilitating conditions, trust) and elaborated on its perceived risks and benefits. Performance expectancy, social influence, and trust predicted acceptance of ANI systems, but only trust predicted acceptance of AGI systems. Overall, the level of acceptance was higher for ANI systems than for AGI systems. Several perceived risks (e.g., risks to mental healthcare, distrust in AI, threats to humanity) and perceived benefits (e.g., benefits to mental healthcare, trust in AI, human help-seeking) were identified. AI systems represent potential avenues for effective suicide prevention. However, to ensure acceptance, AI systems for suicide prevention must be developed in a way that is safe, reliable, and trustworthy.