In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research.
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In this paper we present the first freely available corpus of Dutch text messages containing data originating from the Netherlands and Flanders. This corpus has been collected in the framework of the SoNaR project and constitutes a viable part of this 500-million-word corpus. About 53,000 text messages were collected on a large scale, based on voluntary donations. These messages will be distributed as such. In this paper we focus on the data collection processes involved and after studying the effect of media coverage we show that especially free publicity in newspapers and on social media networks results in more contributions. All SMS are provided with metadata information. Looking at the composition of the corpus, it becomes visible that a small number of people have contributed a large amount of data, in total 272 people have contributed to the corpus during three months. The number of women contributing to the corpus is larger than the number of men, but male contributors submitted larger amounts of data. This corpus will be of paramount importance for sociolinguistic research and normalisation studies.
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Like a marker pen on a map, the Covid-19 pandemic drastically highlighted the persisting existence of borders that used to play an ever decreasing role in people´s perception and behavior over the last decades. Yes, inner European borders are open in normal times. Yes, people, goods, services and ideas are crossing the border between Germany and the Netherlands freely. Yet we see that the border can turn into a barrier again quickly and effectively and it does so in many dimensions, some of them being not easily visible. Barriers hinder growth, development and exchange and in spite of our progress in creating a borderless Europe, borders still create barriers in many domains. Differing labor law, social security and tax systems, heterogeneous education models, small and big cultural differences, language barriers and more can impose severe limitations on people and businesses as they cross the border to travel, shop, work, hire, produce, buy, sell, study and research. Borders are of all times and will therefore always exist. But as they did so for a long time, huge opportunities can be found in overcoming the barriers they create. The border must not necessarily be a dividing line between two systems. It has the potential to become a center of growth and progress that build on joint efforts, cross-border cooperation, mutual learning and healthy competition. Developing this inherent potential of border regions asks for politics, businesses and research & education on both sides of the border to work together. The research group Cross-Border Business Development at Fontys University of Applied Science in Venlo conducts applied research on the impact of the national border on people and businesses in the Dutch-German border area. Students, employees, border commuters, entrepreneurs and employers all face opportunities as well as challenges due to the border. In collaboration with these stakeholders, the research chair aims to create knowledge and provide solutions towards a Dutch-German labor market, an innovative Dutch-German borderland and a futureproof Cross-Border economic ecosystem. This collection is not about the borderland in times of COVID-19. Giving meaning to the borderland is an ongoing process that started long before the pandemic and will continue far beyond. The links that have been established across the border and those that will in the future are multifaceted and so are the topics in this collection. Vincent Pijnenburg outlines a broader and introductory perspective on the dynamics in the Dutch-German borderland.. Carla Arts observes shopping behavior of cross-border consumers in the Euregion Rhine-Meuse-North. Jan Lucas explores the interdependencies of the Dutch and German economies. Jean Louis Steevensz presents a cross-border co-creation servitization project between a Dutch supplier and a German customer. Vincent Pijnenburg and Patrick Szillat analyze the exitence of clusters in the Dutch-German borderland. Christina Masch and Janina Ulrich provide research on students job search preferences with a focus on the cross-border labor market. Sonja Floto-Stammen and Natalia Naranjo-Guevara contribute a study of the market for insect-based food in Germany and the Netherlands. Niklas Meisel investigates the differences in the German and Dutch response to the Covid-19 crisis. Finally, Tolga Yildiz and Patrick Szillat show differences in product-orientation and customer-orientation between Dutch and German small and medium sized companies. This collection shows how rich and different the links across the border are and how manifold the perspectives and fields for a cross-border approach to regional development can be. This publication is as well an invitation. Grasping the opportunities that the border location entails requires cooperation across professional fields and scientific disciplines, between politics, business and researchers. It needs the contact with and the contribution of the people in the region. So do what we strive for with our cross-border research agenda: connect!
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The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
National forestry Commission (SBB) and National Park De Biesbosch. Subcontractor through NRITNational parks with large flows of visitors have to manage these flows carefully. Methods of data collection and analysis can be of help to support decision making. The case of the Biesbosch National Park is used to find innovative ways to figure flows of yachts, being the most important component of water traffic, and to create a model that allows the estimation of changes in yachting patterns resulting from policy measures. Recent policies oriented at building additional waterways, nature development areas and recreational concentrations in the park to manage the demands of recreation and nature conservation offer a good opportunity to apply this model. With a geographical information system (GIS), data obtained from aerial photographs and satellite images can be analyzed. The method of space syntax is used to determine and visualize characteristics of the network of leisure routes in the park and to evaluate impacts resulting from expected changes in the network that accompany the restructuring of waterways.
