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The purpose of this research is to explore how an industry is represented in multimodal public media narratives and to explore how this representation subsequently affects the formation of public sense-giving space during a persisting crisis, such as a pandemic. The question asked is: how do the use of multimodality by public service media dynamically shape representations of industry identity during a persisting crisis?

This study made use of a multimodal approach. The verbal and visual media text on the restaurant industry during the COVID-19 pandemic that were published in Finland by the public service media distributor Yle were studied. Data published between March 2020 and March 2022 were analysed. The data consisted of 236 verbal texts, including 263 visuals.

Three narratives were identified– victim, servant and survivor – that construct power relations and depict the identity of the restaurant industry differently. It was argued that multimodal media narratives hold three meaning making functions: sentimentalizing, juxtaposing and nuancing industry characteristics. It was also argued that multimodal public service media narratives have wider implications in possibly shaping the future attractiveness of the industry and organizational members' understanding of their identity.

This research contributes to sensemaking literature in that it explores the role of power – explicitly or implicitly constructed through media narratives during crisis. Furthermore, this research contributes to sensemaking literature in that it shows how narratives take shape multimodally during a continuous crisis, and how this impacts the construction of industry identity.

This study aims to describe and evaluate various visual and creative tools for supporting the in-depth biographical interview aimed at analyzing educational communities and their stakeholders.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper suggests reflecting on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.

The main contribution of this paper is to unpack the uses and applications of four visual tools that support the interview technique. First, photo-elucidation is presented as a sensory strategy to stimulate the narrative during the dialogical exchange of the interview. Next, the timeline is described as a visual concretization of the traditional biogram widely used in educational research. Next, the authors unravel the uses of the organizational chart in educational research, which, due to its nature and utility, provides a glimpse of the organizational functioning of an institution and is particularly suitable for research in institutional frameworks. Finally, the tool known as the flight of the geese is presented. This tool is recommended for use in educational leadership and teamwork studies due to its simplicity and high representativeness of the hierarchy of roles and functions.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions, and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper invites us to reflect on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram, and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.

We propose in this paper a novel reliable detection method to recognize forged inpainting images. Detecting potential forgeries and authenticating the content of digital images is extremely challenging and important for many applications. The proposed approach involves developing new probabilistic support vector machines (SVMs) kernels from a flexible generative statistical model named “bounded generalized Gaussian mixture model”. The developed learning framework has the advantage to combine properly the benefits of both discriminative and generative models and to include prior knowledge about the nature of data. It can effectively recognize if an image is a tampered one and also to identify both forged and authentic images. The obtained results confirmed that the developed framework has good performance under numerous inpainted images.

This article approaches the possibilities of photo elicitation as a technique for social research in the landscape of technology-mediated instantaneous interpersonal communication.

This case study, which involved persons with prison experience in the process of returning to the community, demonstrates how participant-generated photographs made with mobile handheld electronic devices and the meanings participants have attached to them allowed the research to take a co-creative turn.

The data analyzed show the potential of photo elicitation to build a link between researcher and researched that empowers the latter with agency in designing the results and also throughout the research process as a whole, thus allowing the former to reach a deeper level of understanding of the research participants' social reality.

The research conducted showcases the possibilities of this technique to approach the field of emotions from the ethnography and how they can build knowledge – especially in the work with vulnerable populations in vulnerable contexts – and generate new categories of analysis.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

Many libraries and archives maintain collections of research documents, such as administrative records, with paper-based formats that limit the documents' access to in-person use. Digitization transforms paper-based collections into more accessible and analyzable formats. As collections are digitized, there is an opportunity to incorporate deep learning techniques, such as Document Image Analysis (DIA), into workflows to increase the usability of information extracted from archival documents. This paper describes the authors' approach using digital scanning, optical character recognition (OCR) and deep learning to create a digital archive of administrative records related to the mortgage guarantee program of the Servicemen's Readjustment Act of 1944, also known as the G.I. Bill.

The authors used a collection of 25,744 semi-structured paper-based records from the administration of G.I. Bill Mortgages from 1946 to 1954 to develop a digitization and processing workflow. These records include the name and city of the mortgagor, the amount of the mortgage, the location of the Reconstruction Finance Corporation agent, one or more identification numbers and the name and location of the bank handling the loan. The authors extracted structured information from these scanned historical records in order to create a tabular data file and link them to other authoritative individual-level data sources.

The authors compared the flexible character accuracy of five OCR methods. The authors then compared the character error rate (CER) of three text extraction approaches (regular expressions, DIA and named entity recognition (NER)). The authors were able to obtain the highest quality structured text output using DIA with the Layout Parser toolkit by post-processing with regular expressions. Through this project, the authors demonstrate how DIA can improve the digitization of administrative records to automatically produce a structured data resource for researchers and the public.

The authors' workflow is readily transferable to other archival digitization projects. Through the use of digital scanning, OCR and DIA processes, the authors created the first digital microdata file of administrative records related to the G.I. Bill mortgage guarantee program available to researchers and the general public. These records offer research insights into the lives of veterans who benefited from loans, the impacts on the communities built by the loans and the institutions that implemented them.

This conceptual paper aims to explore government regulatory responses of social networking platforms (SNP) and tourism destination evangelism. This research draws on a two-phase data source review of government legislations that guarantee social media users and empirical papers related to social media platforms. The results revealed that Ghana has adopted specific legislations that manage and control SNP. To the best of the author’s knowledge, this study is the first of its kind that synthesized government legislation and empirical papers on social networking platforms in evangelising destinations which have been missing in extant literature.

Augmented reality (AR) adoption has boomed globally in recent years. The prospective of AR to seamlessly integrate digital information into the actual environment has proven to be a challenge for academics and industry, as they endeavor to understand and predict the influence on users' perceptions, adoption intentions and usage. This study investigates the factors affecting consumers’ behavioral intention to adopt AR technology in shopping malls by offering the mobile technology acceptance model (MTAM).

This conceptual framework is based on mobile self-efficacy, rewards, social influence and enjoyment of existing MTAM constructs. A self-administered questionnaire, constructed by measuring questions modified from previous research, elicited 311 usable responses from mobile respondents who had recently used AR technology in shopping malls. This analysis was performed using SmartPLS3.0.

Grounded on the findings of the study, it was found that, aside from factors such as mobile usefulness, ease of use and social influence, the remaining independent variables had the most significant impact on adopting AR technologies. Considering the limitations of this study, the paper concludes by discussing the significant implications and insinuating avenues for future research.

To better investigate mobile AR app adoption in Pakistan’s shopping malls, the researchers modified the newly proposed MTAM model by incorporating mobile self-efficacy theory, social influence, rewards and perceived enjoyment. However, the extended model has not been extensively studied in previous research. This study is the first to examine the variables that affect an individual’s intention to accept mobile AR apps by using a novel extended MTAM.

Collegiality is the modus operandi of universities. Collegiality is central to academic freedom and scientific quality. In this way, collegiality also contributes to the good functioning of universities’ contribution to society and democracy. In this concluding paper of the special issue on collegiality, we summarize the main findings and takeaways from our collective studies. We summarize the main challenges and contestations to collegiality and to universities, but also document lines of resistance, activation, and maintenance. We depict varieties of collegiality and conclude by emphasizing that future research needs to be based on an appreciation of this variation. We argue that it is essential to incorporate such a variation-sensitive perspective into discussions on academic freedom and scientific quality and highlight themes surfaced by the different studies that remain under-explored in extant literature: institutional trust, field-level studies of collegiality, and collegiality and communication. Finally, we offer some remarks on methodological and theoretical implications of this research and conclude by summarizing our research agenda in a list of themes.

The purpose of this manuscript is to explore an assignment given to students in an online gender and leadership graduate course as a tool to help them think critically about how music influences perceptions of gender roles in both society and leadership.

The assignment directs students to review the current Billboard “Hot 100” chart, which lists the top 100 songs in the United States each week based on sales and streams. Students are prompted to identify a song with gendered themes and discuss how the song portrays women and/or men, what gender stereotypes the song supports or refutes, and whether the messaging is positive or negative in nature. Finally, the students discuss ways that the message in the song could influence the listener’s opinion about gender stereotypes and what effect that could have on gendered leadership issues.

Students use this assignment as an opportunity to apply the course material that relates to the importance of gender representation and the influence of media on gender issues in leadership.

Recommendations are provided to inspire creative ideas for leadership educators who seek to prepare students to understand organizational challenges related to gender issues in leadership.