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This paper aims to undertake an evaluation of the research development and works associated with banking frauds and scams.

The authors have conducted bibliometric analysis of 288 studies on issues of banking frauds and scams, published up to August 4, 2024 using Scopus and the VOS viewer software.

This study disseminates top influential authors, countries, journals, papers, funding institutions and affiliations relating to banking frauds and scams. Generally, although a great deal of work has been accomplished in this area, there are prominent gaps in such findings.

To the best of the authors’ knowledge, this paper is the first comprehensive review of extant research relating to banking frauds and scams. It hence represents an original piece of work in applying bibliometric analysis to this topic area, offering valuable insights for practitioners and academics who seek to understand more about banking frauds and scams risks.

Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).

Michael Gove is a controversial figure, not least due to his time as secretary of state for education under the Cameron coalition government from 2009 to 2013. Gove’s internationalising policy claimed to be addressing the attainment gap between rich and poor, supporting a workforce for the global markets. Gove appealed to all educational leaders by sending them a Gove-signed King James Bible, and he set up a Victorian school desk as the primary display artefact in the Ministry of Education. These two artefacts provide the analytical lens from which the claims and consequences of Gove’s education policy reforms were experienced by educational leaders and schools. This chapter aligns with the editorial line of this book in three ways. First, it acknowledges context as the most important aspect of understanding reform, in this case the neoliberal market economy of Britain in the 21st century. Second, it affords insight into how the selective use of data and political rhetoric acted as a vehicle for power in and through social relations. Finally, it reveals where disadvantage lies and provides impetus for further research and scholarship to mitigate it.

This paper proposes a set of recommendations based upon the limitations found with the application and assessment process to become a Special Constable (SC) with one of the 43 police forces in England and Wales.

Participants were recruited via online social media platforms Twitter and LinkedIn, as well as personal networks and the study was geared towards both respondents who had completed the whole of the application and assessment process, as well as those who may have withdrawn at a particular point or who failed an element of the assessment.

This study yielded several key findings. First, some respondents had limited to no knowledge of the role of the Special Constable, nor of the depth of police work that would be expected of them. Secondly, respondents indicated that they would have benefited from support during the application and assessment process, specifying the advantages that could be derived from a variety of sources such as local force input and workshop sessions. Finally, respondents stated that poor communication from recruiting teams impacted their experience of applying to the Special Constable programmes, causing them to rethink their decision to join.

This research proposes that a far greater input from serving Special Constables during the application and assessment process is key to improving the experiences of candidates, and to their chances of success with the programme.

This study aims to understand client food preferences and how pantry offerings can be optimized by those preferences.

This study develops and administers customized surveys to study three food pantries within the Second Harvest Food Bank of Northwestern North Carolina network. This study then categorizes food items by client preferences, identifies the key predictors of those preferences and obtains preference scores by fitting the data to a predictive model. The preference scores are subsequently used in an optimization model that suggests an ideal mix of food items to stock based upon client preferences and the item and weight limits imposed by the pantry.

This study found that food pantry clients prefer fresh and frozen foods over shelf-friendly options and that gender, age and religion were the primary predictors. The optimization model incorporates these preferences, yielding an optimal stocking strategy for the pantry.

This research is based on a specific food bank network, and therefore, the client preferences may not be generalizable to other food banks. However, the framework and corresponding optimization model is generalizable to other food aid supply chains.

This study provides insights for food pantry managers to make informed decisions about stocking the pantry shelves based on the client’s preferences.

An emerging topic within the humanitarian food aid community is better matching of food availability with food that is desired in a way that minimizes food waste. This is achieved by providing more choice to food pantry users. This work shows how pantries can incorporate client preferences in inventory stocking decisions.

This study contributes to the literature on food pantry operations by providing a novel decision support system for pantry managers to aid in stocking their shelves according to client preferences.

This paper introduces the special issue on Race and Accounting and Accountability. In so doing, it explores racism in its historical and contemporary forms, the role of accounting and accountability in enabling racism and racial discrimination and also efforts of redress and resistance.

We reflect on several critical themes to demonstrate the pervasive and insidious nature of racism and, review the literature on race and racism in accounting, focusing on studies that followed the seminal work by Annisette and Prasad (2017) who called for more research. We also review the six papers included in this special issue.

While many overt systems of racial domination experienced throughout history have subsided, racism is engrained in our everyday lives and in broader societal structures in more covert and nuanced forms. Yet, in accounting, as Annisette and Prasad noted, the focus has continued to be on the former. This special issue shifts this imbalance – five of the six papers focus on contemporary racism. Moreover, it demonstrates that although accounting technologies can and do facilitate racism and racist practices, accountability and counter accounts offer avenues for calling out and disrupting the powers and privileges that underlie racial discrimination and, resistance by un-silencing minority groups subjected to discrimination and injustice.

This introduction and the papers in the special issue offer rich empirical and theoretical contributions to accounting and accountability research on race and racial discrimination. We hope they inspire future race research to nurture progress towards a true post-racial society.

Visually impaired people usually struggle with doing daily tasks due to a lack of visual cues. For image captioning assistive applications, most applications require an Internet connection for the image captioning generation function to work properly. In this study, we developed MyUEVision, an application that assists visually impaired people by generating image captions that can work with and without the Internet. This work also involves reviewing some image captioning models for this application.

The author has selected and experimented with three image captioning models for online models and two image captioning models for offline models. The user experience (UX) design was designed based on the problems faced by visually impaired users when using mobile applications. The application is developed for the Android platform, and the offline model is integrated into the application for the image captioning generation function to work offline.

After conducting experiments for selecting online and offline models, ExpansionNet V2 is chosen for the online model and VGG16 + long short-term memory (LSTM) is chosen for the offline model. The application is then developed and assessed, and the results show that the application can generate image captions with or without the Internet, providing the best result when having an Internet connection, and the image is captured in good lighting with a few objects.

MyUEVision stands out for its both online and offline functionality. This approach ensures the image captioning generator works with or without the Internet, setting it apart as a unique solution to address the needs of visually impaired individuals.