16,108 research outputs found
The Professional Identity of Doctors who Provide Abortions: A Sociological Investigation
Abortion is a medicalised problem in England and Wales, where the law places doctors at the centre of legal provision and puts doctors in control of who has an abortion. However, the sex-selection abortion scandal of 2012 presented a very real threat to 'abortion doctors', when the medical profession's values and practices were questioned in the media, society and by Members of Parliament. Doctors found themselves at the centre of a series of claims that stated doctors were acting both illegally and unethically, driven by profit rather than patient needs. Yet, the perspectives of those doctors who provide abortions has been under-researched; this thesis aims to fill that gap by examining the beliefs and values of this group of doctors. Early chapters highlight the ambiguous position of the abortion provider in Britain, where doctors are seen as a collective group of professionals motivated by medical dominance and medical autonomy. They outline how this position is then questioned and contested, with doctors being presented as unethical. By studying abortion at the macro-, meso- and micro-levels, this thesis seeks to better understand the values of the 'abortion doctor', and how these levels shape the work and experiences of abortion providers in England and Wales. This thesis thus addresses the question: 'What do abortion doctors' accounts of their professional work suggest about the contemporary dynamics of the medicalisation of abortion in Britain?'. It investigates the research question using a qualitative methodological approach: face-to-face and telephone interviews were conducted with 47 doctors who provide abortions in England and Wales. The findings from this empirical study show how doctors' values are linked to how they view the 'normalisation of abortion'. At the macro-level doctors, openly resisted the medicalisation of abortion through the position ascribed to them by the legal framework, yet at the meso-level doctors construct an identity where normalising abortion is based on further medicalising services. Finally, at the micro-level, the ambiguous position of the abortion provider is further identified in terms of being both a proud provider and a stigmatised individual. This thesis shows that while the existing medicalisation literature has some utility, it has limited explanatory power when investigating the problem of abortion. The thesis thus provides some innovative insights into the relevance and value of medicalisation through a comprehensive study on doctors' values, beliefs and practices
Exploring environmental concerns on digital platforms through big data: the effect of online consumers’ environmental discourse on online review ratings
By deploying big data analytical techniques to retrieve and analyze a large volume of more than 2.7 million reviews, this work sheds light on how environmental concerns expressed by tourists on digital platforms, in the guise of online reviews, influence their satisfaction with tourism and hospitality services. More specifically, we conduct a multi-platform study of Tripadvisor.com and Booking.com online reviews (ORs) pertaining to hotel services across eight leading tourism destination cities in America and Europe over the period 2017–2018. By adopting multivariate regression analyses, we show that OR ratings are positively influenced by both the presence and depth of environmental discourse on these platforms. Theoretical and managerial contributions, and implications for digital platforms, big data analytics (BDA), electronic word-of-mouth (eWOM) and environmental research within the tourism and hospitality domain are examined, with a view to capturing, empirically, the effect of environmental discourse presence and depth on customer satisfaction proxied through online ratings
Network Slicing for Industrial IoT and Industrial Wireless Sensor Network: Deep Federated Learning Approach and Its Implementation Challenges
5G networks are envisioned to support heterogeneous Industrial IoT (IIoT) and Industrial Wireless Sensor Network (IWSN) applications with a multitude Quality of Service (QoS) requirements. Network slicing is being recognized as a beacon technology that enables multi-service IIoT networks. Motivated by the growing computational capacity of the IIoT and the challenges of meeting QoS, federated reinforcement learning (RL) has become a propitious technique that gives out data collection and computation tasks to distributed network agents. This chapter discuss the new federated learning paradigm and then proposes a Deep Federated RL (DFRL) scheme to provide a federated network resource management for future IIoT networks. Toward this goal, the DFRL learns from Multi-Agent local models and provides them the ability to find optimal action decisions on LoRa parameters that satisfy QoS to IIoT virtual slice. Simulation results prove the effectiveness of the proposed framework compared to the early tools
Walking with the Earth: Intercultural Perspectives on Ethics of Ecological Caring
It is commonly believed that considering nature different from us, human beings (qua rational, cultural, religious and social actors), is detrimental to our engagement for the preservation of nature. An obvious example is animal rights, a deep concern for all living beings, including non-human living creatures, which is understandable only if we approach nature, without fearing it, as something which should remain outside of our true home. “Walking with the earth” aims at questioning any similar preconceptions in the wide sense, including allegoric-poetic contributions. We invited 14 authors from 4 continents to express all sorts of ways of saying why caring is so important, why togetherness, being-with each others, as a spiritual but also embodied ethics is important in a divided world
How to Be a God
When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers.
Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong.
Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice.
That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer.
The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves?
How should we be gods
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Reliable Decision-Making with Imprecise Models
The rapid growth in the deployment of autonomous systems across various sectors has generated considerable interest in how these systems can operate reliably in large, stochastic, and unstructured environments. Despite recent advances in artificial intelligence and machine learning, it is challenging to assure that autonomous systems will operate reliably in the open world. One of the causes of unreliable behavior is the impreciseness of the model used for decision-making. Due to the practical challenges in data collection and precise model specification, autonomous systems often operate based on models that do not represent all the details in the environment. Even if the system has access to a comprehensive decision-making model that accounts for all the details in the environment and all possible scenarios the agent may encounter, it may be intractable to solve this complex model optimally. Consequently, this complex, high fidelity model may be simplified to accelerate planning, introducing imprecision. Reasoning with such imprecise models affects the reliability of autonomous systems. A system\u27s actions may sometimes produce unexpected, undesirable consequences, which are often identified after deployment. How can we design autonomous systems that can operate reliably in the presence of uncertainty and model imprecision?
This dissertation presents solutions to address three classes of model imprecision in a Markov decision process, along with an analysis of the conditions under which bounded-performance can be guaranteed. First, an adaptive outcome selection approach is introduced to devise risk-aware reduced models of the environment that efficiently balance the trade-off between model simplicity and fidelity, to accelerate planning in resource-constrained settings. Second, a framework that extends stochastic shortest path framework to problems with imperfect information about the goal state during planning is introduced, along with two solution approaches to solve this problem. Finally, two complementary solution approaches are presented to minimize the negative side effects of agent actions. The techniques presented in this dissertation enable an autonomous system to detect and mitigate undesirable behavior, without redesigning the model entirely
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Evaluation of a Remote Implementation of the Well-Being Promotion Program with Middle School Students during COVID-19
The COVID-19 pandemic and pivot to emergency remote teaching changed the way in which many students access school-based mental health interventions. Furthermore, the effects of the pandemic heightened distress and decreased life satisfaction amongst many youth, increasing the need for schools to provide targeted mental health supports (Lazarus et al, 2021; Magson et al., 2021). Empirically supported Tier 2 mental health interventions exist (i.e., the Well-Being Promotion Program; Suldo, 2016), but little is known about how these interventions can be adapted and feasibly implemented in remote school contexts. This retrospective case study evaluated the implementation of a remote version of the Well-Being Promotion Program, a targeted positive psychology intervention, with eighth grade students during the COVID-19 pandemic. The study aimed to (1) to describe the co-design process through which a research-practice partnership modified the WBPP for remote delivery and (2) to explore the implementation strategies that influenced the feasibility of implementing the resulting digital version of the WBPP. The study used qualitative data (e.g., meeting notes, interviews and written feedback from providers, students, and caregivers) and quantitative data (e.g., pre-/post-measures, intervention integrity, attendance) to evaluate the co-design process and the feasibility of the adapted WBPP. Through co-design, the intervention was modified to be facilitated via videoconference, to use digital versions of WBPP materials, to use email to share with caregivers the handouts and a recorded version of the information session, to add additional sessions for data collection, and to adapt language to align with school vernacular. Using reflexive thematic analysis (Braun & Clarke, 2006; Braun et al., 2019), themes were constructed from the data to provide insight into the implementation strategies used by the research-practice partnership to influence feasibility. Findings suggest that (a) maintaining the structure of the WBPP, (b) using technology for remote implementation, (c) collaborating through the research-practice partnership, and (d) recognizing the effectiveness of intervention efforts influenced the feasibility of the remote implementation. Lessons learned from this case study suggest that research-practice partnerships can be critical for influencing the feasibility of intervention implementation in local school contexts, especially during novel situations such as the COVID-19 pandemic
The withdrawal of being and the discursive creation of the modern subject - an examination of the movement form being to non-being through a consideration of Heideggerean and Arsitotelian notions of being
This work considers what it means to 'be' human and seeks to show that it is in the activity of 'being' human that our individual identity lies, because this is the activity that determines what we are and what we will become. Aristotle asked the fundamental metaphysical question, "is a human being idle by nature?" and concluded, from his realisations concerning the dynamic nature of reality, that he is not. Accordingly, the metaphysical vision of 'beinghuman' that Aristotle articulated, which is considered and applied in this work, in contrast to the static notions of being presented by Heidegger and Christian scholasticism, presents an understanding of man as a potentially dynamic and internally active being, capable of maintaining himself by bein~ attuned to reality and thereby contemplating God. It seems most timely to explore Aristotle's understanding of 'being-human' because much postmodern thought seems to be concerned with locating the 'self, or explicating its disappearance in terms of an emancipation from form, or as the exposure of some form of illusion that has kept us all living the lie of selfhood. However, the 'absent' postmodern self finds a place in Aristotle's metaphysical vision, because not only did Aristotle recognise the significance of actively 'being' human, he also recognised that through deprivation and incapacity some forms of being can go out of existence or become something else. And it appears that our postmodern form of unconscious existence constitutes such an altered form, determined according to a deprivation of actively 'being', i.e., by 'non-being.' The determining movement of 'non-being', which emerges from the ontological gap created by failing to 'be', is considered throughout this work, particularly with regard to developments in language and technology, because it is through our single-minded engagement in external productive activities, which are incidental to 'being-human', that we have avoided the inner contemplative activity that inheres in human 'thinghood'
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Privacy-aware Smart Home Interface Framework
Smart home user interfaces are pervasive and shared by multiple users who occupy the space. Therefore, they pose a risk to interpersonal privacy of occupants because an individual’s sensitive information can be leaked to other co-occupants (information privacy), or they can be disturbed by intrusions into their personal space (physical privacy) when the co-occupant interacts with the smart home user interfaces. This thesis hypothesises that interpersonal privacy violations can be mitigated by adapting the user interface layer and presents insights into how to achieve usable user interface adaptation to mitigate or minimise interpersonal privacy violations in smart homes.
The thesis reports two case studies and two user studies. The first case study identifies the key characteristics needed to model the rich context of interpersonal privacy violations scenarios. Then it presents knowledge representation models that are required to represent the identified characteristics and evaluates them for adequacy in modelling the context information of interpersonal privacy violation scenarios. The second case study presents a software architecture and a set of algorithms that can detect interpersonal privacy violations and generate usable user interface adaptations. Then it evaluates the architecture and the algorithms for adequacy in generating usable privacy-aware user interface adaptations. The first user study (N=15) evaluates the usability of the adaptive user interfaces generated from the framework where storyboards were used as the stimulant. Extending the findings from the usability study and expanding the coverage of example scenarios, the second user study (N=23) evaluates the overall user experience of the adaptive user interfaces, using video prototypes as the stimulant.
The research demonstrates that the characteristics identified, and the respective knowledge representation models adequately captured the context of interpersonal privacy violation scenarios. Furthermore, the software architecture and the algorithms could detect possible interpersonal privacy violations and generate usable user interface adaptations to mitigate them. The two user studies demonstrate that the adaptive user interfaces, when used in appropriate situations, were a suitable solution for addressing interpersonal privacy violations while providing high usability and a positive user experience. The thesis concludes by providing recommendations for developing privacy-aware user interface adaptations and suggesting future work that can extend this research
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