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Mixed reality and real-life exercises for mass casualty incidents : a comparison of psychological responses and learning
Get PDFCountering Discrimination in Recruitment: Integrating Blind Recruitment and Bias Awareness Training
No full textThis thesis examines blind recruitment and bias awareness training as strategic tools to combat implicit and explicit bias during hiring processes. Nevertheless, the hiring process may still function as a systemic obstacle in certain cases, preventing diversity and equal opportunities in the workplace. The research utilizes the Dual-Process Theory and Implicit Social Cognition and Social Identity Theory frameworks to analyze how cognitive patterns and social constructs influence the recruitment process. In addition, this research investigates practical results from the Australian Public Service and PricewaterhouseCoopers through case studies to examine the effects of hiring without names and training-based interventions. The international policy review reveals that the two methods (blind recruitment and Unconscious Bias Training) demonstrate potential for bias reduction, but their use as standalone strategies yields limited results. Achieving lasting structural change in recruitment fairness requires data accountability and an inclusive organizational culture as essential elements
Fallauswahl in der qualitativen Forschung : Ein Leitfaden für Studium und Methodenpraxis
No full textTo what extent does profit shifting shape international tax policies, and is the OECD’s BEPS initiative an effective and equitable global response?
No full textMultinational enterprises (MNEs) shift over USD 1 trillion in profits annually to low-tax jurisdictions, causing global tax revenue losses exceeding USD 200 billion (Tørsløv et al., 2023). In response, the OECD introduced the Base Erosion and Profit Shifting (BEPS) initiative, including the Two-Pillar solution, which aims to reallocate taxing rights and enforce a 15% global minimum tax (GMT).
This study evaluates BEPS’s effectiveness, combining macroeconomic data, firm-level analysis, and case studies like the Double Irish Dutch Sandwich. Findings reveal that while BEPS improves tax transparency, it lacks strong enforcement, disproportionately benefits developed nations, and fails to eliminate tax havens.
Although BEPS is a step toward tax fairness, it remains inadequate in preventing aggressive tax planning. Stronger global cooperation, potentially under a UN-led framework, may be necessary to curb profit shifting effectively
Konzeption und prototypische Realisierung von semantischen Modellen zur Datenverarbeitung in verteilten Datenstrukturen öffentlicher Verkehrssysteme
No full textIn dieser Thesis soll die Nutzung semantischer Modelle in der Datenverarbeitung
verteilter Datenstrukturen für die Reiseauskunft im öffentlichen Personenverkehr
beschrieben, sowie dessen Vorteile dargestellt werden. Dies wird im Kern durch die
Präsentation eines Implementierungskonzeptes, sowie dem Beweis der
Realisierbarkeit in Form der Entwicklung eines Prototyps beschrieben werden
Experiences With an In-Bed Real-Time Motion Monitoring System on a Geriatric Ward : Mixed Methods Study
Get PDFDesign and In Vivo Evaluation of an Intraocular Electrode for Ciliary Muscle Biopotential Measurement in a Non-Human Primate Model of Human Accommodation
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Zukunftseuphorie als Trostersatz : Gesellschaftliche Funktionen von Verheißungserzählungen über Künstliche Intelligenz; Vortrag zur 27. Severin-Akademie am 8. Jänner 2025
No full textEvaluating Dimensions of AI Transparency : A Comparative Study of Standards, Guidelines, and the EU AI Act
Get PDFTransparency is considered a key property with respect to the implementation of trustworthy artificial intelligence (AI). It is also addressed in various documents concerned with the standardization and regulation of AI systems. However, this body of literature lacks a standardized, widely-accepted definition of transparency, which would be crucial for the implementation of upcoming legislation for AI like the AI Act of the European Union (EU). The main objective of this paper is to systematically analyze similarities and differences in the definitions and requirements for AI transparency. For this purpose, we define main criteria reflecting important dimensions of transparency. According to these criteria, we analyzed a set of relevant documents in AI standardization and regulation, and compared the outcomes. Almost all documents included requirements for transparency, including explainability as an associated concept. However, the details of the requirements differed considerably, e.g., regarding pieces of information to be provided, target audiences, or use cases with respect to the development of AI systems. Additionally, the definitions and requirements often remain vague. In summary, we demonstrate that there is a substantial need for clarification and standardization regarding a consistent implementation of AI transparency. The method presented in our paper can serve as a basis for future steps in the standardization of transparency requirements, in particular with respect to upcoming regulations like the European AI Act