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This paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.

The study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.

The use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.

Integrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.

This paper explores the challenging nexus of police custody, risk and intra-organisational boundaries in the context of a recently reformed national police service. Police custody is an often-hidden aspect of policing, away from the public gaze and scrutiny. Although there is increasing recognition of the importance of rural policing (e.g. Harkness (2020); Mawby and Yarwood (2011); Ruddell and Jones (2020); Yarwood and Wooff (2016)), there has been little or no focus on rural police custody. This paper seeks to begin to redress this by focussing on the challenges faced by rural police custody in the context of large-scale organisational change.

This paper draws on data from a study funded by the Scottish Institute for Policing Research (2016–2018), entitled “Measuring Risk and Efficiency in Police Custody in Scotland”. The paper adopts a qualitative methodology to develop an understanding of the varying nature of police custody across Scotland. Two contrasting case study locations were selected, one urban and one rural. 12 semi-structured interviews and 15 hours of observation were carried out. Data was transcribed, coded and analysed and thematic analysis enabled themes to be developed. This paper draws on the data from the rural custody suite.

Drawing on the theoretical framework of Giacomantonio (2014) and more recent considerations of abstract policing Terpstra et al. (2019), this paper offers insights into the ways that police custody in rural Scotland has been organised, against the backdrop of challenging organisational change. I argue that as policing services in Scotland have become increasingly “abstract” from communities, police custody as a national division has witnessed the impact of this more greatly than other parts of local policing. Intra-organisational management around staffing has led to complex management of risk, illustrating some of the challenges of national organisational change on police custody.

This paper focuses on the impact of large scale organisational change on rural police custody and intra-organisational relationships and dynamics. Rural policing is still a largely neglected area of study and rural police custody is even less understood. This paper therefore provides an original contribution by focusing on this under-researched area of policing. It also illustrates complexity around risk, staffing and management of people being held in rural police custody suites. It is therefore of value to policing scholars in other contexts, as well as rural criminology more generally. It has applicability to international contexts where macro level policing reform is occurring.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

With a historic lack of attention to synthesis methods such as systematic review and meta-analysis and a lack of randomised controlled trials, the evidence base for behavioural interventions for children and adults who are autistic or are diagnosed with developmental disabilities is patchy. The Sharland Foundation Developmental Disabilities Applied Behavioural Research and Impact Network (SF-DDARIN), a network of like-minded researchers and practitioners across the UK, aims to address this. The purpose of this paper is to describe the network’s work and provide the context for the remaining articles in the special issue that exemplify network projects.

In this case study paper, the authors describe how the SF-DDARIN works and is resourced, detailing the process used to maximise research opportunities by facilitating network members working together. The authors outline the progressive research steps that the SF-DDARIN has identified are needed to develop and improve the evidence base for behavioural interventions systematically and, with examples, describe how the network delivers these steps.

Since its establishment in 2016, the SF-DDARIN network members have collectively worked on more than 53 projects involving over 50 researchers, had over 120 special schools contribute to projects and have recruited over 500 participants. This has been achieved through funding from the Sharland Foundation, primarily to cover the staffing costs of a small support team and internship partnerships with external organisations. Some projects have attracted external funding.

SF-DDARIN may provide an innovative, effective and resource-efficient model for other groups seeking to develop and extend their evidence base in developmental disability research.

Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

This paper highlights how career capital is accrued through three ways of knowing in a women’s leadership programme (WLP) in an Australian State Police Department. A shift in focus to building capability rather than addressing gaps in participants' abilities was enhanced through the unique use of sponsors and positive psychology interventions.

A longitudinal study, which comprised 31 semi-structured in-depth interviews and focus groups, and a survey with participants eight months after the interviews, assessed the impact of enhanced skills, connections and qualifications on extant role performance.

The WLP enhanced three key components of career capital.

The authors' study extends extant knowledge in seven key ways related to WLPs: (1) reaffirms the benefits for police, (2) developing or enhancing career capital, (3) accruing women’s career capital in policing, (4) pedagogical benefits for WLPs, (5) articulating outcomes of developing career capital, (6) the uniqueness of allocating sponsors and (7) extending empirical studies demonstrating synergies within the intelligent career framework.