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In 2015, President Xi Jinping proclaimed the principle of the Sinicization of religions. Since then, it has become the Communist Party's guiding thought in religious governance. However, so far little is known about how it is perceived by everyday religious practitioners, especially Christians. Based on textual analysis of speeches and writings by leaders of the Catholic Church in China, and 50 in-depth interviews with Catholic practitioners from the mainland and Hong Kong, this paper examines how Catholics (en)counter the public transcript created by the state. Church leaders at the national level publicly embrace Sinicization and appropriate the Church's teaching on inculturation, another transcript, as its justification. However, the everyday practitioners interviewed for this study refused to embrace this discourse. Instead, they adopted one of three discursive strategies: rejection, evasion and empathy. All fell short of endorsing the state's discourse. The findings suggest that the Church's transcript enables Catholic practitioners to critically (en)counter the state's transcript.
This chapter seeks to clarify the criminal responsibility that may be imputable to: (i) programmers of autonomous vehicles for related crimes under national criminal law such as manslaughter and negligent homicide and (ii) programmers of autonomous weapons for related crimes under international criminal law, such as war crimes. The key question is whether programmers could satisfy the actus reus element required for establishing criminal responsibility. The core challenge in answering this question is establishing a causal link between programmers’ conduct and crimes related to autonomous vehicles and autonomous weapons. The chapter proposes responsibility for inherent foreseeable risks associated with the use of AVs and AWs on the basis of programmers’ alleged control of the behavior and/or effects of the autonomous vehicles and autonomous weapons. Establishing the exercise of meaningful human control by programmers over autonomous vehicles and autonomous weapons is crucial to the process of imputing criminal responsibility and bridging a responsibility gap.
This chapter analyses robot testimony in criminal proceedings and the problems it poses, primarily through the example of drowsiness alerts generated during an automated automobile ride. A major issue raised by robot testimony is evaluative data, that is, data in which the robot assesses autonomously collected data independently and records its observation. The chapter stresses the importance of vetting robot testimony and identifies deficits in current understandings of the contributions such testimony can make to the truth finding process. The chapter proposes a taxonomy of robot testimony, including evaluative data, as well as a standardized approach for its use in criminal proceedings.
This chapter deals with two possible ways of closing the “responsibility gap” that can occur when AI devices cause harm: holding the device itself criminally responsible and punishing the corporation that employs the device. Robots can at present not be subject to criminal liability because they do not fit into the general scheme of criminal law and cannot feel punishment. But the present scope of corporate criminal responsibility could be expanded to cover harm caused by AI devices controlled by corporations and operating for their benefit. Corporate liability for AI devices should, however, at least require an element of negligence in programming, testing, or supervising the robot.
Robots are with us, but law and legal systems are not ready for them. This book identifies the issues posed by human–robot interactions in substantive law, procedural law, and law’s narratives, and suggests how to address them. When human–robot interaction results in harm, who or what is responsible? Part I addresses substantive law, including the issues raised by attempts to impose criminal liability on different actors. And when robots perceive aspects of an alleged crime, can they be called as a sort of witness? Part II addresses procedural issues raised by human–robot interactions, including evidentiary problems arising out of data generated by robots monitoring humans, and issues of reliability and privacy. Beyond the standard fare of substantive and procedural law, and in view of the conceptual quandaries posed by robots, Part III offers chapters on narrative and rhetoric, suggesting different ways to understand human–robot interactions and how to develop coherent frameworks to do that. This title is Open Access.
Social anxiety and paranoia are connected by a shared suspicion framework. Based on cognitive-behavioural approaches, there is evidence for treating social anxiety and psychosis. However, mechanisms underlying the relationship between social anxiety and paranoia remain unclear.
Aims:
To investigate mediators between social anxiety and paranoia in schizophrenia such as negative social appraisals (i.e. stigma or shame; Hypothesis 1), and safety behaviours (i.e. anxious avoidance or in situ safety behaviours; Hypothesis 2).
Method:
A cross-sectional study was conducted among Asian out-patients with schizophrenia (January–April 2020). Data on social anxiety, paranoia, depression, shame, stigma, anxious avoidance, and in situ behaviours were collected. Associations between social anxiety and paranoia were investigated using linear regressions. Mediation analysis via 10,000 bias-corrected bootstrap samples with 95% confidence intervals (CI) was used to test the indirect effects (ab) of mediators.
Results:
Participants (n=113, 59.3% male) with a mean age of 44.2 years were recruited. A linear relationship between social anxiety and paranoia was found. In multiple mediation analyses (co-varying for depression), stigma and shame (Hypothesis 1) did not show any significant indirect effects with ab=.004 (95%CI=–.013, .031) and –.003 (–.023, .017), respectively, whereas in situ behaviours (Hypothesis 2) showed a significant effect with ab=.110 (.038, .201) through the social anxiety–paranoia relationship.
Conclusions:
Social anxiety and paranoia are positively correlated. In situ safety behaviours fully mediated the social anxiety and paranoia relationship. Targeted interventions focusing on safety behaviours could help reduce paranoia in psychosis. Symptom severity should be measured to help characterise the participants’ characteristics.
The advent of automated driving systems forces us to reconsider legal concepts such as negligence, recklessness, and volition and will lead to new narratives in criminal courts on how to understand these established concepts. New mala prohibita may also need to be developed, impacting human and nonhuman drivers. One question in this reconfiguration will be whose powers of perception and/or agency will be deemed relevant. Automated driving systems have their own hermeneutics in the sense of their algorithms; can, and if so how, will humans understand their actions? Interdisciplinary collaborations are required to deal with new technologies, but jurists are often unacquainted with technology, and the experts who guide them are not usually jurists. Translation problems between disciplines may occur, as well as responsibility gaps, with negative consequences for both new legislation and individual cases. This chapter argues that automated driving systems require a hermeneutics of the situation, a framework to guide factual and legal interpretation for these systems that is interdisciplinary in nature and bridges legal, ethical, and technical challenges.
Unethical behavior among US judges, including sexual misconduct and other forms of discriminatory behavior, is becoming increasingly publicized. These controversies are particularly concerning given the important role judges play in shaping policy pertaining to individual rights. We argue that types of misconduct serve as a signal to the public about potential threats judges may pose to people, particularly groups of people who are marginalized. We use a survey experiment that introduces a judge who has engaged in misconduct to measure if the type of misconduct will influence attitudes on whether the judge poses a threat to the rights of women, racial minorities, and ethnic minorities. Interestingly, we find that judges accused of discriminatory misconduct toward one group are viewed as a threat to rights across the board and are seen as less able to rule fairly on matters pertaining to marginalized people more generally.
Are robots a tool mindlessly following their programming, or an actor with agency? Are robots inevitable to the extent that we should just accept them, or does regulation have a role to play? And how do we understand our understanding, that is, how do we arrive at concepts to understand human–robot interaction that adequately incorporate different disciplines? These questions suggest that to understand robots and our place in the legal world with them, we must consider subject matter beyond substantive law and procedure. The narrative chapters in this Part of the book provide additional ways to identify the questions raised by human–robot interaction and propose how to begin answering them.
Dietary fatty acids (FA) affect metabolic risk factors. The aim of this study was to explore if changes in dietary fat intake during energy restriction were associated with plasma FA composition. The study also investigated if these changes were associated with changes in liver fat, liver stiffness and plasma lipids among persons with non-alcoholic fatty liver disease. Dietary and plasma FA were investigated in patients with non-alcoholic fatty liver disease (n 48) previously enrolled in a 12-week-long open-label randomised controlled trial comparing two energy-restricted diets: a low-carbohydrate high-fat diet and intermittent fasting diet (5:2), to a control group. Self-reported 3 d food diaries were used for FA intake, and plasma FA composition was analysed using GC. Liver fat content and stiffness were measured by MRI and transient elastography. Changes in intake of total FA (r 0·41; P = 0·005), SFA (r 0·38; P = 0·011) and MUFA (r 0·42; P = 0·004) were associated with changes in liver stiffness. Changes in plasma SFA (r 0·32; P = 0·032) and C16 : 1n-7 (r 0·33; P = 0·028) were positively associated with changes in liver fat, while total n-6 PUFA (r −0·33; P = 0·028) and C20 : 4n-6 (r −0·42; P = 0·005) were inversely associated. Changes in dietary SFA, MUFA, cholesterol and C20:4 were positively associated with plasma total cholesterol and LDL-cholesterol. Modifying the composition of dietary fats during dietary interventions causes changes in the plasma FA profile in patients with non-alcoholic fatty liver disease. These changes are associated with changes in liver fat, stiffness, plasma cholesterol and TAG. Replacing SFA with PUFA may improve metabolic parameters in non-alcoholic fatty liver disease patients during weight loss treatment.
Foods consumed at lower eating rates (ER) lead to reductions in energy intake. Previous research has shown that texture-based differences in eating rateER can reduce meal size. The effect size and consistency of these effects across a wide range of composite and complex meals differing considerably in texture and varying in meal occasion have not been reported. We determined how consistently texture-based differences in ER can influence food and energy intake across a wide variety of meals. In a crossover design, healthy participants consumed twelve breakfast and twelve lunch meals that differed in texture to produce a fast or slow ER. A breakfast group (n = 15) and lunch group (n = 15) completed twelve ad libitum meal sessions each (six ‘fast’ and six ‘slow’ meals), where intake was measured and behavioural video annotation was used to characterise eating behaviour. Liking did not differ significantly between fast and slow breakfasts (P = 0·44) or lunches (P = 0·76). The slow meals were consumed on average 39 % ± 9 % (breakfast) and 45 % ± 7 % (lunch) slower than the fast meals (both P < 0·001). Participants consumed on average 22 % ± 5 % less food (84 g) and 13 % ± 6 % less energy (71 kcal) from slow compared with fast meals (mean ± SE; P < 0·001). Consuming meals with a slower ER led to a reduction in food intake, where an average decrease of 20 % in ER produced an 11 % ± 1 % decrease in food intake (mean ± SE). These findings add to the growing body of evidence showing that ER can be manipulated using food texture and that this has aits consistent effect on food and energy intake across a wide variety of Hedonically equivalent meals.