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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.

The present study investigates the effect of foreign direct investment (FDI) and governance quality on carbon emissions in the Economics Community of West African States (ECOWAS).

To achieve the objective of this research, panel data for dependent and explanatory variables over the period 2005–2016, collected in the World Development Indicators (WDI) database and World Governance Indicators (WGI), are analyzed using the generalized method of moments (GMM). Also, the panel-corrected standard errors (PCSE) method is applied to the four segments of the overall sample to analyze the stability of the results.

The findings of this study are: (1) FDI inflows have a negative effect on carbon emissions in ECOWAS and (2) The interaction between FDI inflows and governance quality have a negative effect on carbon emissions. These results show the decreasing of environmental damage by increasing institutional quality. However, the estimation results on the country subsamples show similar and non-similar aspects.

This study suggests that policymakers in the ECOWAS countries should strengthen their environmental policies while encouraging FDI flows to be environmentally friendly.

The subject has rarely been explored in West Africa, with gaps such as the lack of use of institutional variables. This study contributes to the literature by drawing on previous work to examine the role of good governance on FDI and the CO2 emission relationship in the ECOWAS, which have received little attention. However, this research differs from previous work by subdividing the overall sample into four groups to test the stability of the results.

This study was conducted to address the methodical shortcomings and high associated cost of understanding the use of new, poorly understood architectural spaces, such as makerspaces. The proposed quantified method of enhancing current post-occupancy evaluation (POE) practices aims to provide architects, engineers and building professionals with accessible and intuitive data that can be used to conduct comparative studies of spatial changes, understand changes over time (such as those resulting from COVID-19) and verify design intentions after construction through a quantified post-occupancy evaluation.

In this study, we demonstrate the use of ultra-wideband (UWB) technology to gather, analyze and visualize quantified data showing interactions between people, spaces and objects. The experiment was conducted in a makerspace over a four-day hackathon event with a team of four actively tracked participants.

The study shows that by moving beyond simply counting people in a space, a more nuanced pattern of interactions can be discovered, documented and analyzed. The ability to automatically visualize findings intuitively in 3D aids architects and visual thinkers to easily grasp the essence of interactions with minimal effort.

By providing a method for better understanding the spatial and temporal interactions between people, objects and spaces, our approach provides valuable feedback in POE. Specifically, our approach aids practitioners in comparing spaces, verifying design intent and speeding up knowledge building when developing new architectural spaces, such as makerspaces.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.

In February 2018, Jerome Powell had taken over as chair of the FOMC. At first glance, the macroeconomic conditions inherited by Powell appeared favorable for continued stability: unemployment and inflation were low, and the economy had been steadily growing for nearly a decade. Yet despite the appearance of stability, the economy faced significant risks that required the Federal Reserve's attention. Was an uptick in inflation imminent, and if so, should Powell raise rates to limit any inflationary pressure? Or was the economy still operating below capacity, and if so, should the Federal Reserve take a more accommodative stance? To gain perspective, Powell needed to look back at the past fifty years of monetary policy in the United States.

Considering that food security is a global responsibility, the purpose of this study is to examine the impact of agricultural industries on vulnerability to climate change and the moderating effects of gender-diverse parliaments, education expenditures, research and development (R&D) expenditures and foreign direct investment (FDI).

Using concepts in governance, innovation and knowledge theory, a large panel data set of 125 countries covering 1997–2018 (1,852 country-year observations) was analyzed. Data were sourced from the Notre Dame Global Adaptation Index, the World Bank, the Heritage Index and the International Monetary Fund. Moderated random effects regression was conducted in Stata.

The results reveal that agricultural industries are positively associated with vulnerability to climate change and provide support for our predictions that education expenditures and FDI both reduce the impact of agricultural industries on vulnerability to climate change. However, contrary to predictions, the percentage of women in parliament and R&D expenditures both increase this impact.

To the best of the authors’ knowledge, this is the first quantitative study that uses large, established data sets to explore the relationship between agricultural industries and country vulnerability to climate change. This study shows the significance of country-level factors that both decrease and increase the impact of agricultural industries on vulnerability to climate change.

Intrinsic values to the field of special education include advocacy, inclusivity, individuality, and empiricism. From early days of providing custodial care in segregated settings, special education has evolved into a program that seeks to educate students with a wide range of learning needs in inclusive settings and identify a robust research base that informs its policies and practices. Important concepts such as inclusion and continuum of services have not only been valuable in conceptualizing and in providing intervention for students with disabilities but have also been valuable in advancing the field. Research in special education and students with disabilities has been instrumental in moving the field forward. In the future, special education will continue to be valuable in supporting students whose learning and survival needs deviate from the norm in meaningful ways by delivering responsive evidence-based instruction.

The purpose of this paper is to conceptualise a research study to examine leadership as a relational concept between leaders and followers. The context is within surgical practice examining how motivated consultant surgeons are to lead junior doctors and which type of leadership style they use. From a follower perspective, the motivation of junior doctors will be explored, and their leadership preferences will be correlated with those of the actual style of consultant surgeons.

In this paper, the authors provide a detailed description of the methods for an international quantitative research study, exploring sequentially how motivated consultant surgeons are to lead and how leadership styles impact on the motivation of junior doctors. The objectives, method and data collection of this study are explained, and the justification for each method is described.

The findings for this outline study illustrate how critical it is to redefine leadership as a relational concept of leader and follower to ensure adequate support is provided to the next generation of consultant surgeons. Without consideration of the relational model of leadership, attrition will continue to be a critical issue in the medical workforce.

The research limitations are that this is a proposed quantitative study due to the need to collect a large sample of data from surgeons across the UK, Egypt and Germany. This research will have immense implications in developing new knowledge of leadership as a relational concept in medicine and healthcare. This study additionally will impact on how leadership is conceptualised in the curriculum for specialist surgical practice.

The practical implications are that relational leadership is supportive of generating a supportive leadership culture in the workplace and generating more effective teamwork.

To the best of the authors’ knowledge, this is the first study of its kind to look at a relational model of leadership in surgical practice between consultant surgeons and surgical trainees. This study will also identify any specific country differences between the UK, Germany and Egypt.