No description available.

Structural racism has been identified as a major source of medical vulnerability for urban populations. Police brutality is a consequence of structural racism and a critical social determinant of urban health that is associated with both physical and psychological injury. However, the presence of law enforcement agents is common in the healthcare setting, especially in the emergency department. The emergency department occupies a critical social role as a major source of healthcare for vulnerable urban populations, yet very little is known about patients’ opinions regarding police activity in the ED. This study contributes to the growing body of literature on the pathogenic effects of structural racism by designing trauma informed methodology to investigate patient perceptions of police presence in the emergency room. / Urban Bioethics

Black school psychologists are significantly underrepresented in American schools, and this must be addressed to effectively meet the needs of marginalized groups in this field. Through the lenses of critical race theory, intersectionality and the trauma-informed approach, this phenomenological study explored the experiences of eight Black graduate students studying school psychology at both predominantly White institutions (PWIs) and historically Black colleges and universities (HBCUs). Convergent data yielded themes of (1) Awareness of Intersectionality, (2) Black Representation Matters, (3) Black Mentor/Faculty as Support, (4) Black Sociocultural Safe Spaces, (5) Cultural Incompetence at PWI, and (6) Unsupported Traumatic Experiences at PWI. Divergent data revealed that students from HBCUs experienced a sense of belonging, whereas students from PWIs experienced feelings of isolation. Lastly, divergent data revealed that accreditation was the main concern for students who attended HBCUs. Implications, recommendations, limitations, and future research directions are provided. / School Psychology

No description available.

While machine learning has shown success in many fields, it can be challenging when there are limitations with insufficient training data. By incorporating knowledge into the machine learning pipeline, one can overcome such limitations. Therefore, eliciting expert knowledge can play an important role in the machine learning project pipeline. Expert knowledge can come in many forms, and it is seldom easy to elicit and formalize it in a way that is easily implementable into a machine learning project. While it has been done, not much focus has been on how. Furthermore, the motivations for why knowledge was elicited in a particular way as well as the challenges that may exist with the elicitation, are not always focused on either. Making educated decisions for knowledge elicitation can therefore be challenging for researchers. Hence, this work aims to explore and categorize how expert knowledge elicitation has been done by researchers previously. This was done by developing a taxonomy that was then used for analyzing articles. A total of 43 articles were found, containing 97 elicitation paths that were categorized in order to identify trends and common approaches. The findings from our study were used to provide guidance for an industrial case in its initial stage to show how the taxonomy presented in this work can be applied in a real-world scenario.

This study examines how the concepts of biomedical ethics are considered in Islam and how historical Islamic medical scholars treated the concept of ethics in their practice of medicine. Moreover, this research explores the principle of autonomy in biomedical ethics as a factor in Islamic practice of medicine. The issue of autonomy in medical practice is an important topic of discussion requiring examination of the methods of its adaptation and application in Muslim-majority countries. The value and significance of this topic continues at a global level, involving Muslim communities in Non-Muslim countries experiencing religious and social diversity. The fieldwork of this study was conducted in Turkey, Jordan and Gaza Strip, Palestine, investigating the subject matter with practitioners in health care sectors as well as with leading academics, researchers, non-government organizations and policymakers. The results indicate that the principle of autonomy is not fully implemented in the three countries from an Islamic perspective. / 博士(グローバル社会研究) / Doctor of Philosophy in Global Society Studies / 同志社大学 / Doshisha University

Abstract available through the Annals of Behavioral Medicine.

This thesis evaluated the Trauma-Informed Child Advocacy Certificate (TICA) at Mississippi State University which is hosted in the School of Human Sciences, specifically in the area of Human Development and Family Science (HDFS). HDFS students (N = 94) enrolled in coursework during Spring 2021 participated in the evaluation. Students were grouped by enrollment in TICA courses, with 43 students having participated in TICA coursework and 51 students having only participated in general HDFS courses. Assessments included a perceived knowledge survey and 10 application-based scenarios. Independent samples T-tests indicated TICA students perceived themselves to have more trauma-informed knowledge, and frequency analyses showed they were more effective at applying that knowledge than HDFS students who have not taken any TICA courses. Data were used to highlight strengths of the TICA program and make recommendations on ways to enhance the TICA coursework to promote knowledge of trauma-informed professional practices.

No description available.

There is an increasing interest in using deep neural networks in various downstream natural language processing tasks. Such models are commonly used as black boxes, meaning that their decision-making is difficult to interpret. In order to build trust in models, it is crucial to analyse their inner workings which lead to predictions. The need to interpret natural language processing models has induced research on linguistically-informed interpretability. This field revolves around choosing specific linguistic phenomena and inspecting models' capability to capture them without being explicitly trained for it.  This thesis project contributes to the field by assessing the ability of BERT-style models to learn subject number in Lithuanian and English. The experiments revolve around designing diagnostic classifiers which are used to determine if the models are capable of learning this particular linguistic phenomenon. The results show that BERT-style models are capable of implicitly learning the number of a subject both in Lithuanian and English. However, this seems to be harder in Lithuanian, as diagnostic classifiers show a lower accuracy. The study observes that the accuracy of logistic regression diagnostic classifiers fluctuates to a large extent. Fully connected neural network classifiers outperform logistic regression classifiers.