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Racial stigma and racial criminalization have been centralizing pillars of the construction of Blackness in the United States. Taking such systemic injustice and racism as a given, then question then becomes how these macro-level arrangements are reflected in micro-level processes. This work uses radical interactionism and stigma theory to explore the potential implications for racialized identity construction and the development of “criminalized subjectivity” among Black undergraduate students at a predominately white university in the Midwest. I use semistructured interviews to explore the implications of racial stigma and criminalization on micro-level identity construction and how understandings of these issues can change across space and over the course of one's life. Findings demonstrate that Black university students are keenly aware of this particular stigma and its consequences in increasingly complex ways from the time they are school-aged children. They were aware of this stigma as a social fact but did not internalize it as a true reflection of themselves; said internalization was thwarted through strong self-concept and racial socialization. This increasingly complex awareness is also informed by an intersectional lens for some interviewees. I argue not only that the concept of stigma must be explicitly placed within these larger systems but also that understanding and identity-building are both rooted in ever-evolving processes of interaction and meaning-making. This research contributes to scholarship that applies a critical lens to Goffmanian stigma rooted in Black sociology and criminology and from the perspectives of the stigmatized themselves.

The aim of this study is to comprehend the behavioural intention of females' perception toward smart healthcare technology. The study also examines the moderation effect of social influences between perceived smart healthcare technology and perceived usefulness among female users.

To test the model, this study collected data from female respondents (n = 913) responses. The data were analyzed by structural equation modeling (SEM) using Smart-PLS 3.2. To complement the findings from structural equation modeling, the study also conducted a post-hoc test via experimental research design. The authors also applied a t-test and PROCESS macro analysis to re-confirm the relationship mentioned above.

The findings revealed that perceived ease of use significantly mediates the relationship between females' perceived smart healthcare technology and intention to use. The findings also show that social influence moderates between smart healthcare technology and the perceived usefulness relationship.

Social influence is one of the major issues while adopting smart healthcare technology because the respondents perceived that they are accustomed to the technologies related to smart health once their surroundings and social environment influence them.

The current study is a pioneer in the context of a developing country and unique in that it makes two contributions: it extends previous research on smart health technology adoption in the healthcare business by considering females, and it gives a broad knowledge of the female healthcare consumers from emerging nations which can be useful for developing technology-driven healthcare services strategies.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

The purpose of this paper is to use Bourdieu’s Theory of Capital–Field–Habitus to explore how refugees, asylum seekers and migrants accumulate and mobilise social, cultural, symbolic and economic capital to find meaningful work in the Australian construction industry.

The paper reports the results of a survey of refugees, asylum seekers and migrants who have either successfully or unsuccessfully searched for employment in the Australian construction industry.

The findings dispel widely held negative stereotypes of about this group by describing a highly capable workforce which could address significant skills shortages in the industry, while concurrently diversifying the workforce. However, it is found that refugees, asylum seekers and migrants face considerable barriers to finding meaningful employment in the construction industry. In circumventing these barriers, education institutions, charities and community-based organisations play an especially important role, alongside friends and family networks. They do this by helping refugees, asylum seekers and migrants accumulate and deploy the necessary capital to secure meaningful work in the construction industry. Disappointingly, it is also found that the construction industry does little to help facilitate capital accumulation and deployment for this group, despite the urgent need to address diversity and critical skills shortages.

Employing Pierre Bourdieu’s Theory of Capital–Field–Habitus, the findings make a number of new theoretical and practical contributions to the limited body of international research relating to the employment of refugees, asylum seekers and migrant workers in the construction. The results are important because meaningful employment is widely accepted to be the single most factor in the successful integration of refugees, asylum seekers and migrants into a host society and the construction industry represents an important source of potential employment for them.

The post-COVID environment presents significant challenges for organizations. Unfortunately, many leaders and organizations are living in “post-pandemic.” Leaders must reframe their approaches to employee relationships and the nature of the workplace. Employee experience, which combines, user experience, design thinking and organizational development, provides a methodology and perspective that is needed to address these significant changes. The purpose of this paper is to readdress employee experience and how its approach challenges conventional approaches to human resources (HR) and employee engagement and demonstrate how it can serve as an indispensable tool for transitioning to the new workplace.

Employee experience has become ubiquitous in organizations, but unfortunately the underlying sources and philosophies that distinguish this approach are often neglected. This paper demonstrates the new, irreversible organizational world created by COVID-19, reviews the origins of the concept, reviews the six principles previously introduced and then explicates three philosophical paradigmatic shifts that must be undertaken to take advantage of employee experience and address the new organizational challenges.

Employee experience can serve as a strategic tool for addressing post-COVID-19 organizational challenges. Past ideas about engagement will not work. Three shifts deriving from employee experience’s roots in user experiences, design thinking and emergent organization development must be adopted. Instead of thinking structurally in which things are primary, leaders need to take a relational perspective which insists on relational primacy. Because experience is holistic and embodied, a phenomenological perspective must take the place of the usual behavioral perspective. Finally, leaders and HR must see the task ahead as a collaborative codesign with employees, insisting on radical participation.

As with the medical challenges with the COVID-19 virus itself, the organizational challenges are new and have never been faced before. It is difficult to shift paradigms, challenge assumptions and redirect effort while maintaining operating organizations. Often, leaders and organizations are ill-equipped to address very novel situations from past experience and education. Much more research and practical implementations need to be conducted to continue to evolve the concept.

Organizations are facing many crises beyond the supply/demand economic issues caused by COVID-19. The social issues within the organizational world are often overlooked but having significant impact. Cultures have been attenuated and disrupted, employee expectations have changed and the remote job market has expanded opportunities for employment. As a result, retention, performance, loyalty and satisfaction have been negatively impacted. If organizations want to continue growth and productivity, they need to find new ways of working and operating.

The nature of work, organization and employee/organization relationship is in transition. Because much of people’s lives are spent in the workplace, this shift has significant implications for relationships within and beyond the workplace. COVID-19 has also had an impact on mental health, life satisfaction and other aspects of the human experience. Experience in the workplace and outside the workplace are converging and impacting each other. The new reality cannot be ignored or denied.

Many organizations, leaders and HR practitioners are approaching the new reality with outdated and ineffective tools from the pre-COVID-19 world, tools that were questionably effective then. Reclaiming the revolutionary underpinnings of employee experience is a necessary but often neglected action.

The research paper aims to study dissatisfaction of teleworking employees in Spain during the Covid-19 health pandemic in order to propose three models: sociodemographic profile of the teleworking dissatisfied employee; advantages and disadvantages for the teleworking dissatisfied employee and advantages for the teleworking dissatisfied employee.

This study uses official open data obtained from the Spanish National Statistical Institute (INE, 2022) through Decision Trees statistical multivariable models implementing Classification and Regression Trees and Recursive Partitioning and Regression Trees techniques to determine the variables that can influence the satisfaction or dissatisfaction of the subjects.

This investigation offers three models with two sociodemographic profiles of dissatisfied teleworking employee, who is a high/middle-level manager/employee around 45 years old, and she/he lives with the partner. Regarding the most important advantage of teleworking, employees consider “use/saving of time” and as disadvantage “worse organization and coordination of work”.

This research provides empirical evidence with inductive reasoning on understanding the challenges of teleworking dissatisfied employees in Spain not only in turbulent times but also in “normalcy” to improve overall teleworker well-being and accomplish company’s and organization’s long-term objectives for better productivity and effectivity. The study has high practical value due to the integral approach incorporating dissatisfaction as a driver that can trigger negative behaviours towards the organizations and that is seldom addressed in the literature. Additionally, this paper could provide some new ideas for accomplishing “Spain Digital 2025” and “Europe’s Digital Decade: 2030” plans on institutional level.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.