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The purpose of this paper is to explore teacher candidates’ response to young adult literature (prose and comics) featuring fat identified protagonists. The paper considers the textual and embodied resources readers use and reject when imagining and interpreting a character’s body. This paper explores how readers’ meaning making was influenced when reading prose versus comics. This paper adds to a corpus of scholarship about the relationships between young adult literature, comics, bodies and reader response theory.

At the time of the study, participants were enrolled in a teacher education program at a Midwestern University, meeting monthly for a voluntary book club dedicated to reading and discussing young adult literature. To examine readers’ responses to comics and prose featuring fat-identified protagonists, the author used descriptive qualitative methodologies to conduct a thematic analysis of meeting transcripts, written participant reflections and researcher memos. Analysis was grounded in theories of reader response, critical fat studies and multimodality.

Analyses indicated many readers reject textual clues indicating a character’s body size and weight were different from their own. Readers read their bodies into the stories, regarding them as self-help narratives instead of radical counternarratives. Some readers were not able to read against their assumptions of thinness (and whiteness) until prompted by the researcher and other participants.

Although many reader response scholars have demonstrated readers’ tendencies toward personal identification in the face of racial and class differences, there is less research regarding classroom practices around the entanglement of physical bodies, body image and texts. Analyzing reader’s responses to the constructions of fat bodies in prose versus comics may help English Language Arts (ELA) educators and students identify and deconstruct ideologies of thin-thinking and fatphobia. This study, which demonstrates thin readers’ tendencies to overidentify with protagonists, suggests ELA classrooms might encourage readers to engage in critical literacies that support them in reading both with and against their identities.

Access to media is more available now than ever before, both physically and digitally. This study was used to investigate the underlying personality traits that influence the decision to purchase either physical or digital books, and extend theory on access to art and provide a unique lens through which marketers can sell digital media.

Study 1 is a field study in which data were collected from several comic book readers and collectors to look at the role that psychological ownership plays in influencing the likelihood of buying physical or digital comics. Specifically, study 1 includes consumers' need for uniqueness and tech savviness as potential influencers. Study 2 extends the findings of study into a new context and manipulates, rather than measures, the identity of the participants. Study 2 looks at the effects of turning a digital object into a non-fungible token (NFT).

This paper demonstrates that consumers who have a high consumer need for uniqueness (CNFU) are more likely to prefer physical media to digital media. Further, it is shown that preference for physical media leads, on average, to more purchases and that the consumer's psychological ownership mediates the effects of CNFU. In addition, this paper shows that higher degrees of tech savviness led to a preference for digital media. Finally, this paper shows that when consumers identify with a collector identity, turning a digital item into an NFT increases their preference for that object.

This work builds off recent research into physical and digital media and is one of the first to examine the specific personality types that prefer each.

Research on technology acceptance of online entertainment with age, gender and cultural factors as moderator, is rarely conducted. Previous research predominantly focused on age or gender as moderator, neglecting the influence of cultural factors. Therefore, this study aims to investigate acceptance of online entertainment technology, incorporating age, gender and cultural factors as moderator.

Data were collected through a survey comprising 1,121 individuals aged 14–24 years from three cities in Indonesia. The proposed theoretical model examined the causal effect of acceptance and moderating effects due to individual gender, age, power distance, individualism, feminism and uncertainty avoidance (AU). Subsequently, structural equation modeling was used to evaluate the theoretical model, and the results confirmed several findings from previous research.

The findings confirmed the positive direct impact of habit and price value (PV) on behavioral intention and hedonic motivation, as well as social influence on habit. The recent findings derived from the moderating effect analysis showed that age, individualism and feminism played a moderating role in the effects on individual intention due to habit. Additionally, gender and AU moderated the effects on individual habits due to hedonic motivation.

This research contributes to the limited knowledge of technology acceptance of online entertainment, and also integrates the causal effects of individual intention due to habit, PV, hedonic motivation and social influence, considering the moderating role of culture, age and gender. Consequently, the investigation provides valuable insights into the literature by presenting evidence of age, gender and cultural differences in acceptance. Furthermore, it offers practical guidance to online entertainment application developers on designing applications to satisfy consumers of different ages, genders and cultures.

Given the lack of research on the lived experiences of racially minoritized women in academia, this paper provides primary accounts of their experience with impostorization. Impostorization refers to the policies, practices and seemingly innocuous interactions that make or intend to make individuals (i.e. women of color) question their intelligence, competence and sense of belonging.

To explore experiences with impostorization and identify effective coping strategies to counter the debilitating effects of impostorization, 17 semi-structured interviews were conducted with women of color PhD students and faculty at universities throughout the USA and across disciplines.

While impostor syndrome, which refers to feelings of inadequacy that individuals experience and a fear that they will be discovered as fraud, has garnered much attention, the present accounts suggest that the more vexing issue in academia is impostorization, not impostor syndrome. Forms of impostorization include microaggressions, grateful guest syndrome, invisibility and inclusion taxation.

The interviews reveal the implicit and explicit ways in which academia impostorizes racially minoritized women scholars and the coping strategies that they use to navigate and survive within academia. The accounts demonstrate the pernicious effects of labeling feelings of inadequacy and unbelonging as impostor syndrome rather than recognizing that the problem is impostorization. This is a call to change the narrative and go from a fix-the-individual to a fix-the-institution approach.

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/).

To remain sustainable, open source software (OSS) projects must attract new members—or newcomers—who make contributions. In this paper, the authors develop a set of hypotheses based on the knowledge barriers framework that examines how OSS communities can encourage contributions from newcomers.

Employing longitudinal data from the source code repositories of 232 OSS projects over a two-year period, the authors employ a Poisson-based mixed model to test how community characteristics, such as the main drivers of knowledge-based costs, relate to newcomers' contributions.

The results indicate that community characteristics, such as programming language choice, documentation effort and code structure instability, are the main drivers of knowledge-based contribution costs. The findings also suggest that managing these costs can result in more inclusive OSS communities, as evidenced by the number of contributing newcomers; the authors highlight the importance of maintaining documentation efforts for OSS communities.

This paper assumes that motivational factors are a necessary but insufficient condition for newcomer participation in OSS projects and that the cost to participation should be considered. Using the knowledge barriers framework, this paper identifies the main knowledge-based costs that hinder newcomer participation. To the best of the authors' knowledge, this is the first empirical study that does not limit data collection to a single hosting platform (e.g., SourceForge), which improves the generalizability of the findings.

The main aim of this paper is to provide a living tribute of lived expert by experience and researcher Andrew Voyce.

Andrew provided the author with a list of names of people he might approach to write a tribute on his behalf.

The accounts describe the influence that Andrew has had both as an educator and as a trusted colleague for the people approached.

In many ways, the voices of people with mental health problems have been marginalised. Few mental health journals, with only some exceptions, encourage lived experience contributions.

The mental health agenda continues to be dominated by professional groups. The remarkable individuals who continually battle with serious mental illness are often lost in official discourses.

Despite the fact that the topic of mental health is now much more in the public domain, research tells us that the most effective anti-stigma strategy is contact with sufferers.

The archivist Dr Anna Sexton co-produced one of the few mental health archives that only featured people with lived experience. Andrew was one of the four people featured in it. This account “showcases” the work of this remarkable man.

This paper aims to provide a comprehensive overview of existing research on stigma in Arab countries.

A rapid review approach was used, leveraging the Scopus database to identify relevant articles. This streamlined method allows for timely assessments of the current state of knowledge, identifies research gaps and is particularly relevant given the social and cultural dynamics in Arab countries.

This study identified a growing interest in stigma-related topics in Arab countries, with a notable increase in the number of publications and citations over the past decade. Research focused on various aspects of stigma, including mental health, HIV, COVID-19 and diverse health conditions, shedding light on the prevalent challenges faced by different populations. Additionally, comparative studies highlighted the influence of culture and gender on the expression of stigma in the region.

To combat stigma in Arab countries, this study suggests the need for culturally sensitive interventions, integration of mental health services into health-care systems and the development of public health campaigns. These measures should be designed to protect vulnerable populations and prioritize educational initiatives for both the younger generation and health-care professionals.

Reducing stigma in Arab countries is crucial for fostering greater social cohesion, equality and overall well-being. The study underscores the importance of collaborations to adapt successful strategies to the unique Arab context.

This paper fills a crucial research gap by investigating stigma in Arab countries, emphasizing the need for culturally sensitive interventions, education integration and international collaboration to combat it effectively.

This paper investigates school library services in the digital age for students with dyslexia and explores the impact of current library services on students’ learning.

A qualitative study with semi-structured interviews was designed according to the LAFE (Look and listen, Assistance and accessibility, Format and fit, and Environment) framework for learners with dyslexia and the 5E instructional model and conducted with 11 school librarians.

Results indicated that participants lacked knowledge of dyslexia for appropriate library services. Awareness, IT skills, school administration, funding and parental attitudes would influence the library’s tailored services to dyslexic children, despite the rich resources in these participants’ libraries, including paperbacks, digital resources and electronic devices. Adaptations are necessary to provide accessible services, especially by applying digital technologies, and school libraries can positively impact students’ reading interests, promote knowledge inquiry and strengthen information literacy skills.

While students with dyslexia spend significant time in schools, limited studies focus on school library services in the digital age, especially in Asia. This study fills the gap by systematically exploring the issue with the 5E instructional model.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.