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Summary: Leader behavior is essential for creating inclusive organizations. The disruptive context of the COVID‐19 pandemic forced many people to work remotely and leaders to cope with the disruption of their teams' workflows and work arrangements. However, fixed sets of leader behavior as well as stable and shared physical contexts are implicit assumptions in current knowledge and theorizing on inclusive leadership. Therefore, in this study, we first synthesize inclusive leadership literature with leader adaptability and context‐sensitive leadership studies. Next, drawing on 47 interviews with leaders and their followers, we unravel how the enactment of aspired inclusive leadership behaviors was hampered due to the pandemic‐related disruption, and explain how leaders adjusted their inclusive behaviors in response to these difficulties. From these findings, we develop a model that suggests rather than a static set of inclusive leader behaviors, inclusive leadership is enacted through the continuous adjustment on leaders' perceptions of the context and followers' feelings of inclusion. [ABSTRACT FROM AUTHOR]

Qualitative research is important to advance health equity as it offers nuanced insights into structural determinants of health inequities, amplifies the voices of communities directly affected by health inequities, and informs community-based interventions. The scale and frequency of public health crises have accelerated in recent years (e.g., pandemic, environmental disasters, climate change). The field of public health research and practice would benefit from timely and time-sensitive qualitative inquiries for which a practical approach to qualitative data analysis (QDA) is needed. One useful QDA approach stemming from sociology is flexible coding. We discuss our practical experience with a team-based approach using flexible coding for qualitative data analysis in public health, illustrating how this process can be applied to address multiple research questions simultaneously or asynchronously. We share lessons from this case study, while acknowledging that flexible coding has broader applicability across disciplines. Flexible coding provides an approachable step-by-step process that enables collaboration among coders of varying levels of experience to analyze large datasets. It also serves as a valuable training tool for novice coders, something urgently needed in public health. The structuring enabled through flexible coding allows for prioritizing urgent research questions, while preparing large datasets to be revisited many times, facilitating secondary analysis. We further discuss the benefit of flexible coding for increasing the reliability of results through active engagement with the data and the production of multiple analytical outputs. [ABSTRACT FROM AUTHOR]

This study showcases how the Leximancer program can be used to review Leximancer-based research published in tourism and hospitality journals during 2014-2020. Along with a Leximancer-generated concept map, a new tags' association visual analysis was also performed. This innovative method of analysis is a key contribution, as past Leximancer studies in hospitality and tourism have predominantly relied on thematic analysis only. An Insight Dashboard report that is based on Bayesian algebra algorithm in calculating Prominence Scores (PS) for key concepts and compound concepts emergent from the data, supplemented the visual analyses. Thirty-three (33) tourism and three (3) hospitality papers were analysed. The most common tourism context was China and Chinese tourism, and the most prominent phenomena were tourists' experiences, shopping experiences, tourists' evaluations and perceptions. Data for these research studies were predominantly obtained from online reviews, user-generated content (UGC), social media and news media. In the hospitality context, research studies used Leximancer to analyse sentiment, risk factors, and attitudes of frontline hotel employees. Tourism Management and Current Issues in Tourism, had the most papers which used Leximancer. Australian researchers were identified as the leaders in tourism research using Leximancer, followed by lead researchers from Portugal and China. [ABSTRACT FROM AUTHOR]

The use of multi‐sensory data collection tools with children in special and inclusive education is increasing in popularity. Many studies in this area have highlighted the potential for photography, drawings and other visual data collection methods to capture children's perspectives on inclusive practice. However, these tools are likely to be less successful in generating accurate findings if the data arising from them are not effectively interpreted by the researcher. There is a need to highlight appropriate ways to involve child participants as collaborators throughout the research process, with the aim of better accessing the understandings contained in multi‐sensory data collected from children as participants. This paper presents and explores the findings from an empirical participatory study, piloting a multi‐sensory research approach involving children identified with Special Educational Needs and/or Disabilities (SEND) in an English primary school. 'Research conversations' were found to be a highly appropriate way of ensuring that important multi‐perspective understandings contained in visual forms of data are better accessed by the researcher, highlighting the importance of involving child participants as collaborators in an iterative analysis process. [ABSTRACT FROM AUTHOR]

Subsequent analyses of participatory budgeting in Poland emphasise the popularity of environmental issues such as greenery, air quality, and sustainable transport, which should also support objectives in urban climate change adaptation (UCCA). An increasing number of adaptation projects within local standards or ‘green’ civic budgets are often listed among the indicators in urban adaptation plans for Polish cities. However, available research studies and urban evaluation reports show that monitoring participatory budgets poses a methodological challenge. Therefore, the aim of the article is twofold. First, it proposes a method of identifying overlaps of urban climate change adaptation objectives with descriptions of projects submitted to local participatory budgets of the Upper Silesian-Zagłębie Metropolis. For this purpose, a dictionary-based text analysis of project descriptions was performed and critically examined. The second aim was to identify trends in urban climate change adaptation objectives. Thus, the quantitative distribution of coded descriptions was evaluated to investigate how subsequent types of participatory budgets (editions, green vs. standard, implemented vs. non-implemented) differed. The results demonstrate that the available database of participatory budget projects is a rich source of information on local preferences towards issues related to UCCA. To strengthen the objectives of urban climate change adaptation, city administrations can consider additional tools, such as UCCA-related tips/inspiration and targeted calls for projects, as well as supplementing participatory budgets with other deliberative methods. However, collecting precise and calculable data on this topic based on participatory budget databases requires both methodological adjustments and careful validation.

Modern society is experiencing a digital transformation of various spheres associated with the development of artificial intelligence and big data. The introduction of large language models (hereinafter referred to as LLM) into scientific research opens new opportunities, but also raises a number of questions, which makes it relevant to study the peculiarities of their application for qualitative data analysis in sociology. The purpose of this article is to explore how LLM can influence the methodology and practice of sociological research, and to identify the advantages and disadvantages of their application. The authors rely on the use of the Calude-3 LLM to qualitatively analyse empirical data from a sociological study of students’ perception of ­entrepreneurship. The possibilities of LLM in the analysis of qualitative data are revealed: analysis of sentiment, construction of logical conclusions, classification, clustering, and formation of typologies. The advantages of using LLM are shown: increased data processing speed, saving time and resources. The application of LLM becomes a tool to optimise the research process in sociology, allowing to deepen the analysis of qualitative data, but it also has a number of limitations: social and political bias, difficulties with hallucinations. It is necessary to increase the transparency of models, improve their interpretability and explainability and reduce their social and political bias as well as ethical and legal regulation of the use of LLM models.

This article uses a subsample of low-income American Voices Project respondents who rent their homes to examine how households coped with housing insecurity at the onset of the COVID-19 pandemic. First, some renters reported more housing stability because of the expansion of existing programs. However, access to and distribution of these resources was uneven. Second, renters continued to rely on social ties to secure housing but the interpersonal and financial issues that often arise with such arrangements remained during the pandemic. Third, the pandemic provided some renters with reason to request and receive flexibility in payment plans on existing leases, though landlord largess was far from universal. Our findings reveal the limitations of temporary policy responses that are administered in uneven ways, require eligible individuals to seek out and enroll in novel benefit programs, and do not intervene directly in markets to increase supply or control prices.

Despite the abundance of research on the link between teachers’ beliefs and practices, little research has been conducted investigating the relationship between the beliefs of teachers with specific individual attributes and corrective feedback practices. Thus, this study aims to investigate whether growth mindset teachers’ oral corrective feedback (OCF, henceforth) practices are aligned with their beliefs. Eight in-service growth mindset EFL teachers participated in the study. Having collected the data via two questionnaires and a set of classroom observations, MAXQDA software was used to code and quantify the data. The findings showed that growth mindset teachers’ OCF beliefs and their actual OCF practices were aligned in terms of OCF timing. Regarding OCF types, female teachers’ practices were aligned with their beliefs, but male teachers’ beliefs were more incongruent with their practices. Teachers’ beliefs and practices, however, were inconsistent regarding OCF amount and frequency, which can be due to contextual factors, such as occasional time limit. The implications and suggestions for further research are suggested.

Objective: To identify generalism-related competencies that medical students in Japan should acquire in order to provide comprehensive care for patients. Methods: The team responsible for developing the new 'Generalism' section of the 2022 revision of the Model Core Curriculum for Medical Education in Japan (MCC) consisted of nine members from diverse medical backgrounds across Japan. We adopted pragmatism paradigm and analyzed to identify decision-making processes using a qualitative document analysis. Results: The competency list was presented as a four-tier structure. The first tier of generalism was defined as 'take a multi-systemic view of the patient's problems and consider the patient's psychosocial background in order to provide comprehensive, flexible medical care that responds to the needs of the patient and is not limited to one's own specialty, supporting the achievement of individual and societal well-being.' The second tier was framed in terms of 'perspectives' and constructed of four different domains: 'holistic,' 'community,' 'life,' and 'social.' Conclusion: We identified and defined the competencies required by medical students in Japan to provide comprehensive care for patients. By including these competencies in the MCC, undergraduate medical education will be better placed to respond to anticipated changes in the demand for medical care in Japan. Success factors in our guideline development process include facilitating a collaborative and iterative development process, ensuring that diverse perspectives are integrated, and using practical examples and feedback to refine competencies based on a pragmatic approach. [ABSTRACT FROM AUTHOR]

This article uses a subsample of low-income American Voices Project respondents who rent their homes to examine how households coped with housing insecurity at the onset of the COVID-19 pandemic. First, some renters reported more housing stability because of the expansion of existing programs. However, access to and distribution of these resources was uneven. Second, renters continued to rely on social ties to secure housing but the interpersonal and financial issues that often arise with such arrangements remained during the pandemic. Third, the pandemic provided some renters with reason to request and receive flexibility in payment plans on existing leases, though landlord largess was far from universal. Our findings reveal the limitations of temporary policy responses that are administered in uneven ways, require eligible individuals to seek out and enroll in novel benefit programs, and do not intervene directly in markets to increase supply or control prices. [ABSTRACT FROM AUTHOR]

This article investigates the use of wolves to enchant the rationalization of Thompson Manitoba. The city attempted to refocus towards a more touristic economy based around the large wolf population in the surrounding regions. The paper also examines why this attempt at a tourist economy has not produced its intended results. I accomplish this by first discussing the McDonaldization and enchantment of the city. This discussion is framed through George Ritzer and Jeffery C. Alexander's work. I then integrate Umwelt analysis by focusing on Timo Maran's Umwelt mapping to create a comparative approach in which wolf Umwelts within rationalized and enchanted settings can be compared to those in situ. I then make use of qualitative data analysis (QDA) to code a corpus of 50 articles from a local online newspaper that discuss the development of the tourism economy. Accordingly, I apply the theoretical perspectives mentioned to the QDA codes and themes. In the discussion section and conclusion of this paper, I note that wolf Umwelt was largely incompatible with the rationalizing system created within the city and that the use of wolves as enchantment relied on motifs of overly hyperreal intersubjectivity between humans and wolves. Consequently, collective representation regarding the tourist initiative was not constructed by this rationalization and enchantment. [ABSTRACT FROM AUTHOR]

Fostering Environmental Citizenship (EC) through science education equips students with competences needed for action-taking on sustainability issues. Quantitative studies show Dutch student EC competences are lacking compared to international averages. This study provides a qualitative view on Dutch 11-15 year old students' EC, providing support for science teachers. The research question is: What are main characteristics of Dutch lower secondary student competences around environmental citizenship? We conducted semi-structured interviews with 42 students (F: 25, M: 17; average age 13.3). Questions concerned student sustainability knowledge, attitudes, behavior, and reflection. Common trends in the data are a worry for the future, the experienced distance from sustainability issues, and interest in personal actions. Students do not discuss sustainability with friends. They adopt a form of EC that can be typified as personally responsible citizenship. Our data provide qualifiers for conclusions from quantitative studies that previously dominated our understanding of student EC. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop autonomous artificial intelligence agents capable of working as a cohesive group to solve intricate decision-making processes, ultimately pushing the boundaries of artificial intelligence’s applicability in high-stakes and real-world scenarios. An autonomous multi-agent model was designed and deployed using the Analytic Hierarchy Process (AHP) decision-making framework, with autonomous AI agents, such as CrewAI and AutoGen, orchestrating multiple stages of activities performed by four distinct agents leveraging generative AI (GenAI). These agents were applied to a use case for proof of concept. The agents used a qualitative dataset to generate management recommendations based on cost and market feasibility considerations. The model was tested with publicly available customer feedback data on oatmeal cookies. It synthesized 913 customer reviews, identified common complaints, provided a summary of potential solutions, and generated a summary of market opportunities, along with relevant challenges. Although a subject matter expert's review is necessary to evaluate the practicality and relevance of the recommendations, the results demonstrated the high potential of multi-agent models in synthesizing and distilling large datasets into actionable insights, thereby augmenting decision-making processes in business contexts. The model's modular design allows for enhancements in quality, accuracy, and practicality by incorporating additional datasets and new agents. This study underscores that the integration of GenAI within a multi-agent model empowers businesses to swiftly transform vast amounts of business intelligence data into practical recommendations.

Purpose – This study investigated the visibility of carbon emissions allowances accounting in the financial reports of 32 clean development mechanism (CDM) projects in the UAE to uncover the obstacles to setting consistent standards for carbon emission accounting. As carbon emissions are monetized as credits, consistent accounting standards can aid decision-makers in the development of carbon emission mitigation strategies. Design/methodology/approach – This study used a grounded theoretical framework for exploring the terms used in the policy documents of international accounting bodies regarding accounting standards and guidelines for carbon emission credits. Raw qualitative data were gathered, and an inductive approach was used by analyzing documents from various sources using the qualitative data text analysis software QDA Miner 6. Findings – The findings showed that the financial statement reports of the corporations did not include disclosure of the carbon credit account. This omission was due to the lack of global standardization of carbon credit accounts and emission allowance recognition. This may hinder the production of a comprehensive report containing accurate and valuable financial information relevant to all stakeholders. Originality/value – The study is among the first to use a grounded theoretical framework to investigate whether corporations are applying common standards and guidelines for carbon emissions accounting.

Visual art can enhance wellbeing and quality-of-life; however, the experience of visual art for people with mild-to-moderate vision loss has not been examined. Eight participants (6 females, 2 males; Mean age = 81 years, SD = 7.9, range 70–91 years; 4 with mild vision loss and 4 with moderate vision loss based on binocular visual acuity) completed a mixed-methods study comprising: a semi-structured interview on visual art experience; an eye examination; and questionnaires about visual functioning and quality-of-life. Various themes were identified: visual perception of art (e.g. altered colours, visual distortions, etc.), viewing conditions, elements of art, personal preference, deriving meaning, appreciation of art, impact of impaired visual perception, and social aspects of art. The overall experience of art is influenced by how an individual sees, perceives, and makes meaning from art. Even mild vision loss can impair this experience and impact emotional and social wellbeing. [ABSTRACT FROM AUTHOR]

An initial coin offering (ICO) seeks to raise initial investments for companies by selling crypto tokens to individuals interested in crowdfunding. As ICOs have gained popularity, a lack of information regarding startup companies' prior financial status and business health has led to information asymmetry between potential investors and ICO projects. This study explores the informational cues necessary to bridge this gap. Employing signaling theory, we elucidate the presence of information asymmetry and conduct two case analyses to identify relevant informational cues. Twitter data from two ICO projects (Stratis and NEO), which achieved the highest return on investment at the time of data collection, are extracted and analyzed to identify informational themes. Our findings reveal multiple and distinctive themes of informational cues for each ICO project, demonstrating that transmitted signals vary across different stages and are generated by both the coin publisher and the public. This research illuminates the flow of informational cues between ICO initiators and potential investors on social media. By analyzing online communication threads using qualitative methods, this study significantly contributes to the understanding of information asymmetry in the context of ICOs. [ABSTRACT FROM AUTHOR]

Despite the abundance of research on the link between teachers’ beliefs and practices, little research has been conducted investigating the relationship between the beliefs of teachers with specific individual attributes and corrective feedback practices. Thus, this study aims to investigate whether growth mindset teachers’ oral corrective feedback (OCF, henceforth) practices are aligned with their beliefs. Eight in-service growth mindset EFL teachers participated in the study. Having collected the data via two questionnaires and a set of classroom observations, MAXQDA software was used to code and quantify the data. The findings showed that growth mindset teachers’ OCF beliefs and their actual OCF practices were aligned in terms of OCF timing. Regarding OCF types, female teachers’ practices were aligned with their beliefs, but male teachers’ beliefs were more incongruent with their practices. Teachers’ beliefs and practices, however, were inconsistent regarding OCF amount and frequency, which can be due to contextual factors, such as occasional time limit. The implications and suggestions for further research are suggested. [ABSTRACT FROM AUTHOR]

The value of coaching teachers by professional coaches in their school context is recognized to provide them with sustainable professional development (SPD). However, little is known about the coaching process promoting SPD and the variables that can explain its quality. Three objectives were pursued: 1) to describe the quality of the coaching process; 2) to determine the characteristics of the coach, and 3) to identify the characteristics of the school context that can explain quality to promote SPD. An Embedded Multiple-Case Study Design was conducted at two different schools. Results describe that the quality of the coaching process was clear in its orientation to precise goals, its complexity, and its dynamism. The coaches' characteristics that can explain the quality of the coaching process to promote SPD are their perceptions of the context and their conceptions. The most important characteristic of the context that can reveal the quality of coaching enacted is the leadership of the school principal and the teachers' culture of collaboration. [ABSTRACT FROM AUTHOR]

Measuring the impact of land use regulation on the land market involves identifying and classifying relevant impact factors related to the land market. The objective of this study was to identify land market impact factors in the context of the introduction of land use regulation in Nepal. Through a combination of desktop review and the incorporation of stakeholder perspectives, the paper presents a new approach for determining land market impact factors due to land use regulation where both generic and country issues are considered. A desktop review was carried out to identify a preliminary set of impact factors, which were reclassified through intuitive analysis based on the degree of thematic closeness. Perspective-based impact factors were identified through the qualitative analysis of primary data collected through semi-structured interviews with the Nepalese land market stakeholders. These independently derived impact factors were compared with the desktop literature review impact factors, resulting in 14 land market impact factors across four dimensions, including transaction cost, valuation, mortgage availability, taxation, and compensation across the economic dimension; lot size, subdivision restrictions, and coordination across the institutional dimension; awareness, expectation, and proximity across the social dimension; and risk reduction, quality of residential land, and suitability of zoning classification across the environmental dimension. There was significant overlap and commonality across factors identified from both the literature review and semi-structured interviews. The land market impact factors determined in this study may be adapted and generalized across other countries and could be utilized to better understand the impacts of land policy decisions on urban planning and development. Further research is recommended on the process to operationalize the use of these factors to quantify the impact of land use regulation on different land markets. [ABSTRACT FROM AUTHOR]

To contribute to healthcare improvements, qualitative health research must adapt to the demanding pace of constantly changing healthcare practices and policies. To meet this challenge, researchers need methods for rigorous and rapid data analysis. This article introduces the Rapid Group Analysis Process (Rap-GAP), a new approach for rapid qualitative data analysis. This method is more efficient than other rapid qualitative analysis methods. It allows for the direct involvement of diverse participants in the analysis process, including patients or healthcare decision-makers with limited qualitative research experience, while keeping the analysis grounded in the primary data (e.g., transcripts). These attributes make Rap-GAP a unique and valuable alternative to traditional qualitative analysis. This article describes the 5-step Rap-GAP process and 3 case studies that demonstrate how to use the method and adapt it for different analytical goals. Future research will evaluate and describe the outcomes of Rap-GAP compared to traditional qualitative analysis. [ABSTRACT FROM AUTHOR]

Copyright of Bartin University Journal of Faculty of Education is the property of Bartin University Journal of Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In the dynamic field of qualitative research, a contentious issue persists: Is digital software a more effective tool for research analysis than the manual method? To shed light on this debate, we undertook quasi-experimental research, focusing on our study's unique contribution to exploring the capabilities of both methods in analysing health datasets. Objective: Our study aims to compare the effectiveness of qualitative analysis between researchers who are proficient in digital software and those skilled in the manual method. We seek to understand which method is more effective in data analysis. Methodology: We employed a quasi-experimental design and a purposive sampling approach to select our study participants. These participants (n=150) were then divided into two groups: those proficient in digital software and those skilled in the manual method. We then conducted an intervention in which participants analysed a qualitative dataset using their preferred method. The data collected was then analysed using quantitative measures, such as percentages, central tendency measures, and independent samples t-tests. Results: The t-test result showed that statistically significant differences exist between the two groups across all indicators (all Ps

There are many elements of qualitative data analysis that may appear intangible to novice researchers. In this article, I present an approach to a data analysis workshop with students, where I do my best to avoid the instruction to "fold in the cheese," as per the television series Schitt's Creek. Students attend 90-minute workshops where they use an assortment of buttons to practice different strategies of qualitative analysis. The tactile mechanism of sorting objects has proven invaluable in workshops, as it helps students to physically organize their thoughts and takes pressure off to find the "right" answer. The nature of the items could also be adapted to meet students' accessibility needs. The workshop has improved the quality of student writing in methods chapters and built students' confidence as they approach their own data analysis processes, especially for master's students and research assistants, where a full-length course may not be feasible. [ABSTRACT FROM AUTHOR]

Qualitative researchers can benefit from using generative artificial intelligence (GenAI), such as different versions of ChatGPT--GPT-3.5 or GPT-4, Google Bard--now renamed as a Gemini, and Bing Chat--now renamed as a Copilot, in their studies. The scientific community has used artificial intelligence (AI) tools in various ways. However, using GenAI has generated concerns regarding potential research unreliability, bias, and unethical outcomes in GenAIgenerated research results. Considering these concerns, the purpose of this commentary is to review the current use of GenAI in qualitative research, including its strengths, limitations, and ethical dilemmas from the perspective of critical appraisal from South Asia, Nepal. I explore the controversy surrounding the proper acknowledgment of GenAI or AI use in qualitative studies and how GenAI can support or challenge qualitative studies. First, I discuss what qualitative researchers need to know about GenAI in their research. Second, I examine how GenAI can be a valuable tool in qualitative research as a co-author, a conversational platform, and a research assistant for enhancing and hindering qualitative studies. Third, I address the ethical issues of using GenAI in qualitative studies. Fourth, I share my perspectives on the future of GenAI in qualitative research. I would like to recognize and record the utilization of GenAI and/or AI alongside my cognitive and evaluative abilities in constructing this critical appraisal. I offer ethical guidance on when and how to appropriately recognize the use of GenAI in qualitative studies. Finally, I offer some remarks on the implications of using GenAI in qualitative studies. [ABSTRACT FROM AUTHOR]

To address global and local issues, the development of education on international social work and international social welfare is required in Japan. This study aims to identify the trends in and content of subjects related to international social welfare at national and public universities in Japan and use the findings to develop subject design. National, prefectural and other public universities that offered subjects related to international social welfare (n = 11) were selected for a syllabi analysis. The objectives and goals of each subject and the content of each planned class were coded through inductive content analysis by using qualitative data analysis software (MAXQDA). Common perspectives and topics were found despite the varying subject content. The findings concerning subject objectives and goals indicated that sample syllabi tended to include a multifaceted perspective and a view of relativisation. Based on the findings, we developed a subject design that includes a 'glocal' perspective on international social work. [ABSTRACT FROM AUTHOR]

This article aims to describe a new coding and data analysis method for qualitative researchers, especially in education and health inquiry. We label this method Heroic Coding, a proposal for understanding the role of education and health personnel in apocalyptic scenarios. We propose this method as a subtype within Literature and Language Coding methods described in Saldaña's The Coding Manual for Qualitative Researchers. Heroic Coding employs, in the first cycle coding, an eclectic strategy and, in the second cycle, an elaborative strategy to refine conceptual dimensions about heroes and heroic subjectivities. This article uses a data set from empirical research in education policy enactments to illustrate Heroic Coding in action. Furthermore, we reflect on future possibilities and limitations of this coding method for qualitative research in apocalyptic conditions. [ABSTRACT FROM AUTHOR]

Copyright of Japanese Journal of Physical Education & Sport for Higher Education / Daigaku Taiiku Supotsugaku Kenkyu is the property of Japanese Association of University Physical Education & Sports and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Details findings from a project on the potential for arts activities and art therapy to support the mental health and wellbeing of children living in Kashmir. The intervention engaged 30 school children over the course of one year who produced various forms of artwork and performances. In this paper, we report on project impacts, drawing on some of our qualitative measures including observations and interviews. Our research details impacts and improvements in areas of emotional expression, belonging, and agency. We also found an important role for schools to create safe, secure, and caring spaces to allow students to express themselves and work through traumatic feelings in a non-judgemental way. School-based arts interventions can play an important role in the mental health and wellbeing of children. Critical here, however, are dedicated space, time, and resources to provide a supportive environment and to sustain activity in long-term. [ABSTRACT FROM AUTHOR]

In this article, we address data interrelations that social researchers face when working with qualitative data collected through in-depth interviews with longitudinal (QLR) and multiperspective (MPR) research designs. Revisiting data from four different research projects and building on the proposal by VOGL, ZARTLER, SCHMIDT and RIEDER (2018), we present the 4C model of complexities within data interrelations. Specifically, the broader pool of data allowed us to cross-investigate how interview data may contradict, correct, complement, or be confluent with what the researcher has gathered from another interview conducted at a different point in time (longitudinally) or with another study participant (multi-perspective approach). Using different forms of transitions (e.g., transitions to adulthood, migratory transitions, transitions to parenthood) as a common analytical thread, we argue that revealing inherent inconsistencies in the data reflects the complex and ever-changing nature of reality and that making sense of these inconsistencies often enriches interpretations. [ABSTRACT FROM AUTHOR]

The rapid development of artificial intelligence and large language models (LLMs) has led to significant advancements in applying machine learning techniques across diverse disciplines, including educational science research. This study investigates the potential of LLMs like ChatGPT for qualitative data analysis, focusing on open, axial, selective coding, theme or pattern identification, and inter-rater reliability. Our findings indicate promising capabilities of ChatGPT in open coding, demonstrating accurate categorization of qualitative data. However, axial coding posed challenges due to the model's limited understanding, which was partially addressed by refining prompts based on ChatGPT's interpretation. ChatGPT also showed competence in selective coding and theme or pattern identification, providing additional insights. For inter-rater reliability, ChatGPT's performance varied across datasets, with improvements observed when providing contextual information. It is important to note the limitations and variability of LLMs such as ChatGPT, which is in public beta and subject to potential limitations in usage and reliability. Our study demonstrates ChatGPT's potential for coding and inter-rater reliability. Improved results are achieved with refined prompts and utilising ChatGPT's own definitions. The adoption of LLMs for qualitative analysis requires further exploration, including addressing algorithmic bias and the potential for inaccurate responses. Validation techniques are crucial in mitigating these risks. [ABSTRACT FROM AUTHOR]

Bu araştırmanın temel amacı, dijital göçebeler perspektifinden Türkiye imajını anlamaya çalışmaktır. Son yıllarda sayısı gittikçe artan dijital göçebeler, zamandan ve mekandan bağımsız şekilde çalışan, aynı zamanda seyahat eden yeni bir turist-işçi grubunu ifade etmektedir. Gittikleri ülkelere ekonomik katkı sağladıkları için çekici bir grup haline gelen dijital göçebeler, destinasyonları ziyaret etmeden önce kendi toplulukları ile yoğun iletişim halindedir. Gitmek istedikleri destinasyonlar hakkında tavsiyeler alan ya da tavsiyeler veren dijital göçebeler için ülkeler hakkında oluşturulan imajlar tercih edilebilirlik noktasında anlam taşımaktadır. Dijital göçebelerin aktif şekilde kullandığı Nomad List sitesi ve Reddit dijital göçebe topluluğu üzerinden verileri toplayan bu araştırma, nitel analiz stratejilerinden içerik çözümlemesini seçmiştir. Araştırma sonuçlarına göre Türkiye, döviz üzerinden geliri olan kişiler açısından uygun yaşam maliyeti sunan, mutfak kültürü ve doğal güzellikler bakımından zengin ve sıcakkanlı insanlara sahip bir ülke olarak çekici bir imajla algılanmıştır. Ülkenin olumsuz imajında ise İngilizce konuşma oranının çok düşük olması, anti-demokratik yapı ve enflasyon kaynaklı fiyatların artış göstermesi gibi özellikler yer almıştır.

In this article, we address data interrelations that social researchers face when working with qualitative data collected through in-depth interviews with longitudinal (QLR) and multi-perspective (MPR) research designs. Revisiting data from four different research projects and building on the proposal by VOGL, ZARTLER, SCHMIDT and RIEDER (2018), we present the 4C model of complexities within data interrelations. Specifically, the broader pool of data allowed us to cross-investigate how interview data may contradict, correct, complement, or be confluent with what the researcher has gathered from another interview conducted at a different point in time (longitudinally) or with another study participant (multi-perspective approach). Using different forms of transitions (e.g., transitions to adulthood, migratory transitions, transitions to parenthood) as a common analytical thread, we argue that revealing inherent inconsistencies in the data reflects the complex and ever-changing nature of reality and that making sense of these inconsistencies often enriches interpretations.

This article discusses the alignment of framework analysis with a critical realist philosophy in qualitative analysis. Whilst both are used in social sciences and prioritise meaning making of complex phenomena, the two approaches have not been combined prior to the study outlined in this article. The article describes critical realist ontology and epistemology, the implications of this philosophy for data analysis and the structured processes of framework analysis. Using an example from a study of youth programmes in Aotearoa/New Zealand, the article demonstrates the value of framework analysis for critical realist studies. Emphasis is placed on the capacity of framework analysis to support varied foci on data, theory, and different modes of inferencing which are used in critical realist studies to provide an explanatory account of data. [ABSTRACT FROM AUTHOR]

A recent group cognitive behavioral therapy (gCBT) intervention for dysmenorrhea conducted by our team demonstrated feasibility, acceptability, and preliminary efficacy at reducing menstrual pain. This study aimed to use qualitative analyses to explore participants' reflections about the intervention's group dynamic. Participants included 20 young women ages 18–24 years with average menstrual pain of 8.0 (SD = 1.1) on a 0–10 (0 = none, 10 = worst pain possible) numeric rating scale. Semi-structured individual and group interviews were conducted after the intervention. Researchers then conducted deductive, iterative thematic analysis using a template analysis approach. Two themes were generated: benefit and logistics. The benefit theme included two sub-themes: (1) camaraderie (an emotional, psychological, or social connection between participants); and (2) sharing (information, advice, or experiences). The logistics theme highlighted how the structure of the group influenced the dynamic and was divided into two sub-themes according to the time frame being described: (1) reactions (participants' experiences with how the group dynamic was facilitated); and (2) future (how the group structure could be improved). Results of this study contribute to the growing body of literature related to gCBT for pain conditions. Future research is needed to optimize the group dynamic and evaluate its specific therapeutic role in the treatment. [ABSTRACT FROM AUTHOR]

Social scientific work on argumentation is yet to address the perennial tension between social cognition and social constructionism. Moreover, argumentation‐based qualitative analysis protocols are needed for interview and textual data. Nonetheless, argumentation models remain too complex to reflect everyday argumentation and are not necessarily reflective of underlying cognitive processes. This presents the need for further theorising social behaviour, with a view to formulating a model of argumentation that (a) is parsimonious, and (b) aligns with the literature on joint projects, due to the fact that in social cognition terms, argumentation is for doing. In this paper, we draw upon interdisciplinary literature on argumentation, noting convergences among different approaches. We then proceed to consider the socio‐cognitive bedding provided by Lay Epistemic Theory, to present our Minimal Model of Argumentation (MMA). In MMA, interlocutors are held to make claims concerning an issue of concern, and defend them using warrants, evidence and qualifiers. We end by providing empirical examples supporting the utility of our model in qualitative research. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Theory & Practice in Education (JTPE) / Eğitimde Kuram ve Uygulama is the property of Journal of Theory & Practice in Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The potential use of artificial intelligence programs such as a ChatGPT to analyze qualitative data raises any number of questions, most notably whether it is possible to produce similar results without the demanding process of manual coding. In addition, there are questions about both the simplicity of using ChatGPT for qualitative data analysis and the potential time savings that it might provide This article addresses these questions by using ChatGPT to reinvestigate two qualitative datasets that were previously analyzed by more traditional methods. In particular, it examines the extent to which the responses from ChatGPT can recreate the themes that were originally chosen to summarize the two previous analyses. The results show that ChatGPT performed reasonably well, but in both cases it was less successful at locating subtle, interpretive themes, and more successful at reproducing concrete, descriptive themes. In doing so, the program was quite easy to use and required very little effort in comparison to approaches that rely on manual coding. It is important to recognize, however, that both coding and approaches based on artificial intelligence are simply tools that must be applied within a larger analytic process. Overall, this exploration suggests that artificial intelligence may well have the power to disrupt the coding of data segments as a dominant paradigm for qualitative data analysis. [ABSTRACT FROM AUTHOR]

Ekwusigo local government council is a bureaucratic organization that ought to implement essential public policies while maintaining professionalism and other attributes of bureaucracy. However, poor staff training and development culture affected this function. The specific objective of this research was to identify the necessary strategies for effective manpower training in Ekwusigo local government council of Anambra State, Nigeria. The research adopted survey research design. The research submitted that the purpose of manpower training in Ekwusigo local government area should center on improving quality of workforce, improving employee growth, preventing obsolescence, assisting new comer, bridging the gap between planning and implementation, enhancement of health and safety measures, and increasing workers morale cum enthusiasm. Regarding the specific objective, result shows that the appropriate strategies towards manpower development in Ekwusigo Local Government Council are significant. In conclusion, the findings predicate that the optimal performance of Ekwusigo local government is dependent upon the adoption of these identified strategies for training and re-training of the council's employees. It recommended that manpower development should be encouraged by the council leadership for the members of staff of Ekwusigo local government council. [ABSTRACT FROM AUTHOR]

Copyright of Social Sciences Studies is the property of Social Sciences Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Online Journal of Recreation & Sports is the property of Online Journal of Recreation & Sports and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Selcuk Communication / Selcuk Iletisim is the property of Journal of Selcuk Communication and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)