Dworkin on external skepticism and moral permissions

This article discusses Ronald Dworkin’s first objection against what he calls external moral skepticism, the view that denies truth-value to moral judgments. According to that objection, an external skeptic denies that substantive moral judgments can be true. But, at the same time, the objection goes, what follows from the skeptical view is that all actions are morally permissible, which is in itself a substantive moral judgment. We call this ‘the self-defeating argument.’ We argue that the objection’s success depends on how we interpret the idea of moral permission, an issue Dworkin does not clearly resolve. Against his objection, we advance two different arguments. First, once we learn what role the idea of moral permission plays in morality, we can see that any plausible view of some agent’s moral permission must acknowledge its complex character, and that the existence of a moral permission must have some impact on the balance of moral reasons for other agents. On this understanding, it is false that it follows solely from external skepticism that everything is permissible. Second, we argue that even if permissions have a simple character, not a complex one, they are plausible only when framed within a moral constellation of rights and obligations. So understood, it is, again, false that it follows from external skepticism that everything is permissible.     

Deep learning for sex determination: Analyzing over 200,000 panoramic radiographs

The objective of this study is to assess the performance of an innovative AI-powered tool for sex determination using panoramic radiographs (PR) and to explore factors affecting the performance of the convolutional neural network (CNN). The study involved 207,946 panoramic dental X-rays and their corresponding reports from 15 clinical centers in São Paulo, Brazil. The PRs were acquired with four different devices, and 58% of the patients were female. Data preprocessing included anonymizing the exams, extracting pertinent information from the reports, such as sex, age, type of dentition, and number of missing teeth, and organizing the data into a PostgreSQL database. Two neural network architectures, a standard CNN and a ResNet, were utilized for sex classification, with both undergoing hyperparameter tuning and cross-validation to ensure optimal performance. The CNN model achieved 95.02% accuracy in sex estimation, with image resolution being a significant influencing factor. The ResNet model attained over 86% accuracy in subjects older than 6 years and over 96% in those over 16 years. The algorithm performed better on female images, and the area under the curve (AUC) exceeded 96% for most age groups, except the youngest. Accuracy values were also assessed for different dentition types (deciduous, mixed, and permanent) and missing teeth. This study demonstrates the effectiveness of an AI-driven tool for sex determination using PR and emphasizes the role of image resolution, age, and sex in determining the algorithm's performance.     

北美数字政府跨国工作组及其研究初步进展

介绍了北美数字政府跨国工作组(North Amnerica Digital Government working Group)的研究目标及其第一年的工作进展.北美数字政府跨国工作小组创建于2007年,得到了美国国家科学基金(NSF)数字政府研究项目及美国、加拿大、墨西哥等其他有关机构的资助.该工作组旨在推动跨地域、跨政府的数字政府研究.在第一年所开展的工作中,该工作组成员共在美国、加拿大及墨西哥举行了3次会议,分享了各自的研究专长和兴趣,并通过这些初步互动,取得了一些学术成果.该工作组设立了"跨边境整合与联动""全信息产品标价网络"两个课题研究小组,介绍了两个小组在第一年的工作进展情况.     

School Engagement in Times of Confinement: A Stress Process Approach

Journal of Youth and Adolescence - The first COVID-19 confinement induced dramatic changes in the lives of adolescents, but little is known about the processes that affected youth engagement with...     

COVID-19 Pandemic and Intimate Partner Violence: an Analysis of Help-Seeking Messages in the Spanish-Speaking Media

The role of the Spanish-speaking media is crucial for how Latinx communities learn about seeking help when experiencing intimate partner violence (IPV). This study investigated the IPV help-seeking messages disseminated by the Spanish-speaking media in the U.S. during the COVID-19 pandemic. We engaged in an exploratory content analysis of videos from Univision’s main website, the most-watched Spanish-speaking media network in the U.S. We searched for videos related to IPV help-seeking posted from March 19–April 21, 2020—including the weeks after the World Health Organization declared COVID-19 a global pandemic and the U.S. mandated a shelter-in-place. After assessing inclusion criteria, 29 videos were analyzed. Data were analyzed using basic content analysis to determine frequencies and inductive interpretive content analysis to code for help-seeking messages. We identified eight manifest messages related to seeking help when experiencing IPV in times of a crisis: (1) contact a professional resource; (2) contact law enforcement; (3) contact family, friends, and members of your community; (4) create a safety plan; (5) don’t be afraid, be strong; (6) leave the situation; (7) protect yourself at home; and (8) services are available despite the pandemic. We found that the manifest messages alluded to three latent messages: (1) it is your responsibility to change your circumstances; (2) you are in danger and in need of protection; and (3) you are not alone. IPV and media professionals should ensure a structural understanding of IPV in their help-seeking messages and avoid perpetrating stigmatizing and reductionist messages.

     

Development of a Questionnaire on Intentions to Engage in Dating Violence Among Puerto Rican Residents

Journal of Family Violence - This mixed-methods paper describes the development and preliminary validation of the Behavioral Intentions Questionnaire (BIQ), a multi-scale questionnaire developed to...     

Structural Topic Models for Open‐Ended Survey Responses

Collection and especially analysis of open‐ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it incorporates information about the document, such as the author's gender, political affiliation, and treatment assignment (if an experimental study). This article focuses on how the STM is helpful for survey researchers and experimentalists. The STM makes analyzing open‐ended responses easier, more revealing, and capable of being used to estimate treatment effects. We illustrate these innovations with analysis of text from surveys and experiments.     

BUILDING ENFORCEMENT CAPACITY: EVIDENCE FROM THE MEXICAN CIVIL SERVICE REFORM

Building enforcement capacity, that is, attaining and sustaining control in order to implement changes, is crucial for the success of public management reforms. However, this aspect of public management reform does not receive much theoretical or empirical attention. This paper analyzes the process of building enforcement capacity for the case of the Mexican Professional Civil Service reform. Although this reform experienced several complications (e.g., limited support, resources, and credibility), important goals were attained and some control was achieved. We study how officials attained control over implementation through the adaptive management of combinations of different types of control strategies (regulatory, normative, and procedural). The case study, focused on the analysis of in‐depth interviews with the highest officials involved in the implementation of this reform, finds evidence for three combinations of strategies next to a general pattern characterized by a trade‐off between compliance and coordination. This trade‐off shows that the process of building enforcement capacity may affect the goals of the reform, deviating from lawmakers' original intentions Copyright © 2014 John Wiley & Sons, Ltd.     

Negotiated peace versus victor's peace: the geopolitics of peace and conflict in Sri Lanka

In examining the failure of the 2002 peace process between the Sri Lankan government and the Liberation Tigers of Tamil Eelam (LTTE), this essay argues for the need to go beyond the power dynamics of the local actors. The peace process was dismantled and military victory by the Sri Lankan government made possible not so much by the Sinhala nationalist discourse, which opposed administration of development aid by the LTTE, as by the global security discourse associated with geo-strategic interests. The EU-led development discourse, which was informed by the liberal internationalist ethos, could have facilitated resolution and transformation of the conflict. In its place a security-based, realist discourse was prioritized in South Asia by the UK and US governments, particularly after the invasions of Afghanistan and Iraq. This was the discourse which provided the material basis for the Sinhala nationalists to consolidate their power in pursuing a military victory. The post-war era is marked by geopoliticization of the human rights discourse, deepening the conflict. This essay explores the correlation between the liberal peace model, human rights, international relations and geopolitics.