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This study examines how the representation of women and people of color on nonprofit boards relates to CEO gender and race.

This study uses the 2020 data of 501(c)(3) nonprofit organizations in a Southeastern U.S. state. It employs the seemingly unrelated bivariate probit regression to simultaneously estimate the two equations for CEO gender and race.

The findings show that the proportion of board members of color is positively associated with having a CEO of color and a female CEO. The proportion of female board members is positively associated with having a female CEO, but not with having a CEO of color.

The lack of a positive connection between women’s representation on the board and having a CEO of color may be attributable to the pervasive and systematic Whiteness in nonprofit leadership. The findings suggest that nonprofit boards reflect on the current executive hiring policies and practices to address existing racial biases or barriers.

This study’s findings reveal that the descriptive representation of women and people of color in the governing board is closely linked to their substantive representation in the form of selecting a woman or a person of color as the CEO. The findings also suggest an interconnection between the representation of people of color on the board and having a female CEO. However, women’s representation on the board is not related to having a CEO of color.

This study examines how users' multidimensional representational fidelity factors affect sociability and cyberself engagement in the Metaverse platform; that is, how they interact with newly defined self-images as their personas in the environments. It investigates how representational fidelity serves platform users to perform social roles and increase their sociability by establishing a new cyberself, thus influencing continuous platform use.

This study surveyed 314 users of the Metaverse platform Horizon, where users can create a virtual agent avatar, meet people in the same online environment in real time, and interact with a sense of three-dimensional immersion. Data were analyzed using partial least squares regression models.

User socialization significantly influenced the intention to use the Metaverse platform. Representational fidelity was a crucial variable for sociability, and activity representational fidelity was the most influential aspect among the four other elements. Platforms should consider how to enable users to create and use activities that faithfully represent their personas.

The novelty of this study is that it introduces representational fidelity based on representation theory into the context of virtual persona in the Metaverse platform. This study extended representational fidelity to the socialization perspective by utilizing the integrated model of user satisfaction and the technology acceptance model. Through the results, this study emphasized that users' sociability significantly influences their intention to use the Metaverse platform. Finally, this study provides a feasible guideline on how practitioners could design and strengthen their platforms so that users can represent their cyberselves faithfully.

Allied Health Professionals (AHPs) are the third largest professional group in the National Health Service (NHS). This qualitative study aimed to establish the representation of AHPs at NHS Trust board level.

Examination of public Trust board minutes and Care Quality Commission (CQC) reports from a sample of NHS provider Trusts in the West Midlands. One reviewer extracted data concerning all details pertaining to professional staffing groups.

A stark picture of under-representation which is statistically significant emerges. AHP representation to Trust boards via public board meetings was 7% for AHPs, compared to 41% for doctors and 52% for nurses. There were similar results with CQC reports, with the representation of AHPs at 11%, whilst doctors and nurses were significantly higher at 42 and 47%, respectively.

The data gathered for this paper was from a small number of NHS provider Trusts in the West Midlands of England, which can be considered a limitation of the study. However, the results of this study are stark and provide a compelling snapshot of the significant under-representation of AHPs to those NHS Trust boards included.

AHPs are a significant staff group within the NHS; their representation at board level is of benefit to the Trust boards both in terms of engaging with staff and in terms of managing quality and risk. Recommendations are made that Trust boards ensure they have a board member with responsibility for AHPs who actively engages with, understands and provides challenge, and that the CQC considers the inclusion of examples of AHP activity and staffing levels in their inspection, and that these are confirmed with senior AHPs in the organisation being inspected.

This is an original paper and is the first to address the representation of AHPs at Trust board via consideration of board papers and CQC reports, providing a platform for further consideration.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.

As a fairy tale is adapted to fit with current cultural discourses, drastic changes occur. One of these changes is the erasure of the old man. The wise old man, the doddering old fool, and many more tropes that older men fill have been altered. The eccentric Merlin and the mad Hatter have been replaced with younger versions in Merlin (2008–2012) and the Syfy miniseries Alice (2009). While the grandfather is technically found in Disney's Once Upon a Time in the form of Rumpelstiltskin, it is rarely discussed. In the Beauty and the Beast (2017), Maurice is no longer the town oddity as he goes from tinkering with odd inventions, to being a music box maker. His creativity and quirky idiosyncrasies have been erased.

This chapter delves into this disappearance of the older man in modern fairy tale adaptations, and the repercussions this has in the representation for the older man. Furthermore, this chapter seeks to show how toxic ageist notions in Hollywood have impacted the role of the old man as he is replaced with the stereotypical younger man, due to the increased objectification of men in film and the subsequent conformity to the ‘ideal masculine form’. This objectification can be seen through the slow ‘reinvigoration’ of the Mad Hatter from Disney's Alice in Wonderland (1951) to the Hatter in Syfy's Alice (2009), Johnny Depp's Mad Hatter, Tarrant Hightopp, in Tim Burton's Alice in Wonderland (2010), and finally Sebastian Stan's Mad Hatter in Once Upon a Time (2011–2018).

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

This chapter considers the modes and politics of refugee representation, and the function of art and literature as sites of resistance to, or the reinforcing of, dehumanising or idealised tropes of people seeking refugee protection. Specifically, the chapter addresses the connection between dehumanised representations of the imagined refugee and the violence and ‘logic’ of Australia’s offshore detention regime in Nauru and Papua New Guinea. In engaging with these issues, the chapter draws on Manus Prison Theory and its focus on who gets to represent refugee experience, and to generate knowledge about it and on what terms. It considers these questions through an examination of two contrasting art projects, which alternately raise and contest the idea of the ‘deserving refugee’. In exploring these questions, the chapter also engages with the temporalities of refugee representation and the role of crisis in generating ‘stock’ refugee representations. It ultimately argues that the politics of refugee representation are central to questions of refugee and migrant justice, and further, that we cannot separate contemporary forms and representations of violence against refugees from colonial and neocolonial acts of sovereignty and expulsion.

Research on Traveller education in Ireland is limited. Internationally, studies on the education of the Traveller, Roma or Gypsy community tend to focus on educational participation and exclusion, discrimination, identity and belonging with little focus on the representation of Traveller student across different types of schools and educational settings. This chapter examines the distribution of Traveller students across mainstream and alternative education settings in Ireland, and how this distribution varies across different types of schools and centres. Using data from the Growing Up in Ireland principal survey and survey data from Irish alternative education providers (The National Youthreach Programme), it explores the concentration of Travellers in mainstream provision, in designated disadvantaged schools (Delivering Equality of Opportunity in Schools [DEIS]) compared to non-DEIS schools, and alternative education in Ireland. Findings show a higher representation of Traveller students in schools designated disadvantaged compared to non-disadvantaged settings and greater numbers of Traveller students in large primary and, to a lesser extent, secondary schools. The findings for alternative education show that Traveller young people make up 15% of learners which is higher than their representation in the general population or the school system. There is marked regional variation with higher representation of Travellers in alternative education settings in the West of Ireland compared to other regions.

With increasing policy emphasis on inclusive education and the need to increase retention of students from Traveller backgrounds, it is perhaps an opportune time to explore the distribution of Traveller students across different school and alternative educational contexts so that educational supports can be targeted more effectively.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

Given the relevance of female directors in the governance of any firm, this paper aims to examine their effect on firms’ financial performance by investigating their general impact and segregating the same into different subgroups based on Kanter’s theory.

To achieve the purpose, this study selects a sample of the top 100 listed Indian firms for the period of 2014–2018 and gathers the data pertaining to the variables under consideration from the respective firms’ annual report and corporate database Capitaline Plus. For undertaking the investigation, the authors have segregated the sample into three groups, i.e. firms with boards having less than 10% of female directors are called skewed boards; firms with boards having female directors that range from 10% to 20% are called as tilted board; and firms with boards having sizable representation of female directors of above 20%. To examine the performance impact of overall female directors and their different subgroups, the authors have used a generalized estimating equation model. For the robustness test, the authors have used the fixed-effect model.

The authors find a significant positive impact of the overall percentage of female directors on the financial performance of firms. Additionally, the results indicate that boards with a titled group of female directors and boards with a sizable representation of female directors significantly positively impact firms’ performance. However, the authors fail to extricate any significant performance impact of boards with a skewed group of female directors.

First, the study reveals that despite prevailing nepotism in India, female directors, owing to their core characteristics, can create a favorable perception of firms in the market. Second, it also works as an eye-opener for regulators by revealing the minimum threshold for female directors that a board should have to exploit the benefits of a gender quota rather than mere compliance with the requirements of the Companies Act, 2013. Third, it implies that more gender-diverse boards can improve a firm’s financial performance only if female directors range between the thresholds of 10% to 20%. Finally, the finding is significant for changing the business culture in India, where institutions are traditionally less supportive of women than in other emerging countries.

Departing from existing studies, which provide evidence on the performance impact of the overall percentage of female directors, the study unveils the differential impact of female directors on firms’ financial performance depending on their level of representation on the board. To the best of the authors’ knowledge, this is the first study in the context of an emerging market to test Kanter’s theory.