Conscience of a Catholic Judge

Symposium theme — Evolving Standards of Decency in 2003: Is the Death Penalty on Life Support

The Meaninglessness of the Plain Meaning Rule

The contemporary lawyer and judge confront, in the mine run of their daily work, a mountain of statutes. In an unprecedented way, law today is statute law, and few legal problems have escaped the tender mercies of the legislature. Statutory interpretation is a daily and pressing task for virtually every lawyer. And yet, there is no generally accepted consistent theory to guide this work. The late Henry Hart and Dean Albert Sacks argue forcefully, [T]he hard truth of the matter is that American courts have no intelligible, generally\u27 accepted, and consistently applied theory of statutory interpretation. \u27 This conclusion is embedded in several hundred pages of case excerpts proving the point beyond dispute. Good legal theory is not an intellectual luxury. If we lack good theory, we will be unable to explain judicial decisions and consumers of the output of our court systems will not believe they have been justly treated. Without the discipline of good theory, we cannot even critique and reform our own work product as lawyers. My thesis in this article is that the so-called plain meaning rule is not only wrong in itself, but is also a major stumbling block hindering the adoption of a sound theory of statutory interpretation. Legal thinking in terms of the rule, whether to follow it or to find an exception, structures our whole approach to statutory interpretation; its repudiation is a present necessity. I wish in this article to summarize criticisms of the plain meaning rule, suggest why it has survived despite criticism, and sketch a theory and practice of statutory interpretation which should replace it

Memetic Algorithms Beat Evolutionary Algorithms on the Class of Hurdle Problems

Memetic algorithms are popular hybrid search heuristics that integrate local search into the search process of an evolutionary algorithm in order to combine the advantages of rapid exploitation and global optimisation. However, these algorithms are not well understood and the field is lacking a solid theoretical foundation that explains when and why memetic algorithms are effective. We provide a rigorous runtime analysis of a simple memetic algorithm, the (1+1) MA, on the Hurdle problem class, a landscape class of tuneable difficulty that shows a “big valley structure”, a characteristic feature of many hard problems from combinatorial optimisation. The only parameter of this class is the hurdle width w, which describes the length of fitness valleys that have to be overcome. We show that the (1+1) EA requires Θ(n w) expected function evaluations to find the optimum, whereas the (1+1) MA with best-improvement and first-improvement local search can find the optimum in Θ(n 2 +n 3/w2 ) and Θ(n 3/w2 ) function evaluations, respectively. Surprisingly, while increasing the hurdle width makes the problem harder for evolutionary algorithms, the problem becomes easier for memetic algorithms. We discuss how these findings can explain and illustrate the success of memetic algorithms for problems with big valley structures

The online inverted classroom model (oICM): a blueprint to adapt the inverted classroom to an online learning setting in medical and health education [version 2]

This article was migrated. The article was marked as recommended. The idea of this paper is to offer a blueprint, to guide educators setting up a complete digital teaching scenario according to the latest insights of educational research. The COVID-19 pandemic forced higher education institutions all around the world to radically shift their curricula from a mix of face-to-face and remote teaching methods to a fully remote curriculum. Though challenging, this time provides opportunities to implement new educational methods and to improve the quality of digital teaching. The concept of the inverted classroom was modified to meet the special needs of the new online settings. The proposed online Inverted Classroom Model (oICM) includes the following phases: (1) pre-phase, (2) self-learning-phase, (3) synchronous online phase, (4) transfer-phase, and (5) evaluation. Recommendations and potential tools are provided for each phase. The oICM is an innovative and easy to use approach to shape digital teaching and learning processes during and after the COVID-19 pandemic. This blueprint is developed by the committee “Digitalization” of the German Association for Medical Education (GMA), mainly for educators who are familiar with the Inverted Classroom Model (ICM) or similar blended learning formats

Methodology to Assess Clinical Liver Safety Data

Analysis of liver safety data has to be multivariate by nature and needs to take into account time dependency of observations. Current standard tools for liver safety assessment such as summary tables, individual data listings, and narratives address these requirements to a limited extent only. Using graphics in the context of a systematic workflow including predefined graph templates is a valuable addition to standard instruments, helping to ensure completeness of evaluation, and supporting both hypothesis generation and testing. Employing graphical workflows interactively allows analysis in a team-based setting and facilitates identification of the most suitable graphics for publishing and regulatory reporting. Another important tool is statistical outlier detection, accounting for the fact that for assessment of Drug-Induced Liver Injury, identification and thorough evaluation of extreme values has much more relevance than measures of central tendency in the data. Taken together, systematical graphical data exploration and statistical outlier detection may have the potential to significantly improve assessment and interpretation of clinical liver safety data. A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials

Random Geometric Graphs

We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size of the largest cluster. We derive an analytical expression for the cluster coefficient which shows that the graphs are distinctly different from standard random graphs, even for infinite dimensionality. Insights relevant for graph bi-partitioning are included.Comment: 16 pages, 10 figures. Minor changes. Added reference

Socioeconomic factors, sleep timing and duration, and amygdala resting-state functional connectivity in children

IntroductionReduced sleep health has been consistently linked with increased negative emotion in children. While sleep characteristics have been associated with neural function in adults and adolescents, much less is known about these associations in children while considering socioeconomic context. In this study, we examined the associations among socioeconomic factors, sleep duration and timing, and resting-state functional connectivity (rsFC) of the amygdala in children.MethodsParticipants were typically-developing 5- to 9-year-olds from socioeconomically diverse families (61% female; N = 94). Parents reported on children’s weekday and weekend bedtimes and wake-up times, which were used to compute sleep duration and midpoint. Analyses focused on amygdala-anterior cingulate cortex (ACC) connectivity followed by amygdala-whole brain connectivity.ResultsLower family income-to-needs ratio and parental education were significantly associated with later weekday and weekend sleep timing and shorter weekday sleep duration. Shorter weekday sleep duration was associated with decreased amygdala-ACC and amygdala-insula connectivity. Later weekend sleep midpoint was associated with decreased amygdala-paracingulate cortex and amygdala-postcentral gyrus connectivity. Socioeconomic factors were indirectly associated with connectivity in these circuits via sleep duration and timing.DiscussionThese results suggest that socioeconomic disadvantage may interfere with both sleep duration and timing, in turn possibly altering amygdala connectivity in emotion processing and regulation circuits in children. Effective strategies supporting family economic conditions may have benefits for sleep health and brain development in children