The Role of Apparent Constraints in Normative Reasoning: a Methodological Statement and Application to Global Justice

The assumptions that are made about the features of the world that are relatively changeable by agents and those that are not (constraints) play a central role in determining normative conclusions. In this way, normative reasoning is deeply dependent on accounts of the empirical world. Successful normative reasoning must avoid the naturalization of constraints and seek to attribute correctly to agents what is and is not in their power to change. Recent discourse on global justice has often come to unjustified conclusions about agents obligations due to a narrow view of what is changeable and by whom.I would like to thank for their helpful comments Christian Barry, Rudiger Bittner, Darrel Moellendorf and Thomas Pogge.     

Life-Prolonging Killings and their Relevance to Ethics

What makes killing morally wrong? And what makes killing morally worse than letting die? Standard answers to these two questions presuppose that killing someone involves shortening that person's life. Yet, as I argue in the first two sections of this article, this presupposition is false: Life-prolonging killings are conceivable. In the last two sections of the article, I explore the significance of the conceivability of such killings for various discussions of the two questions just mentioned. In particular, I show why the conceivability of life-prolonging killings renders Frances M. Kamm's attempt to provide an answer to the second question problematic.     

Constrained maximum likelihood estimation of two-level covariance structure model via EM type algorithms

In this paper, the constrained maximum likelihood estimation of a two-level covariance structure model with unbalanced designs is considered. The two-level model is reformulated as a single-level model by treating the group level latent random vectors as hypothetical missing-data. Then, the popular EM algorithm is extended to obtain the constrained maximum likelihood estimates. For general nonlinear constraints, the multiplier method is used at theM-step to find the constrained minimum of the conditional expectation. An accelerated EM gradient procedure is derived to handle linear constraints. The empirical performance of the proposed EM type algorithms is illustrated by some artifical and real examples.This research was supported by a Hong Kong UCG Earmarked Grant, CUHK 4026/97H. We are greatly indebted to D.E. Morisky and J.A. Stein for the use of their AIDS data in our example. We also thank the Editor, two anonymous reviewers, W.Y. Poon and H.T. Zhu for constructive suggestions and comments in improving the paper. The assistance of Michael K.H. Leung and Esther L.S. Tam is gratefully acknowledged.     

Closing the gap between behavior and models in route choice: The role of spatiotemporal constraints and latent traits in choice set formation

A considerable gap exists between the behavioral paradigm of choice set formation in route choice and its representation in route choice modeling. While travelers form their viable choice set by retaining routes that satisfy spatiotemporal constraints, existing route generation techniques do not account for individual-related spatiotemporal constraints. This paper reduces the gap by proposing a route choice model incorporating spatiotemporal constraints and latent traits. The proposed approach combines stochastic route generation with a latent variable semi-compensatory model representing constraint-based choice set formation followed by compensatory choice. The model is applied to data focusing on habitual commuting route choice behavior in morning peak hours. Results show (i) the possibility of inferring spatiotemporal constraints from considered routes, (ii) the importance of incorporating spatiotemporal constraints and latent traits in route choice models, and (iii) the linkage between spatiotemporal constraints and time saving, spatial and mnemonic abilities.     

Fabricated Illness: Working within the Family System to Find a Pathway to Health

The term medically unexplained symptoms refers to a clinical presentation where the child's symptoms and impairment cannot be explained by any known organic pathology, and may include conversion disorders, somatoform pain disorders, factitious disorder, and factitious disorder by proxy. In this case study, we present our treatment of a 9‐year‐old girl with a 2‐year history of medically unexplained abdominal cramping and vaginal discharge. During the 9 months that we worked with this family, we were never able to clarify in our own minds the source of the child's symptoms—that is, who was responsible for their induction or who was the instigator or maintainer of the exaggerated symptoms. Nor did we come to fully understand the function of the symptoms in the family system. Our case report does not answer either of these questions. Instead, we describe how we worked with the family despite the ongoing ambiguities as to why the symptoms were occurring and who was inducing them. The functional outcome was disappearance of symptoms, return to full school attendance, and improved parenting behavior.     

Women’s everyday mobility: Frightening situations and their impacts on travel behaviour

This paper investigates frightening situations women face in their everyday mobility. The focus is not on serious criminal offences but rather on all situations causing fear such as harassment and the influence on the travel behaviour of women. Two surveys were conducted in Austria in 2012 and 2013 to assess whether and how many women are affected and to get insights in locations of the incidents and the circumstances. The personal security aspects of different modes of transport are investigated. The results show that women who experienced frightening situations tend to avoid certain destinations or routes and travel modes more than other women. The results also confirm that women in general have constrained travel behaviour because of fear about their personal security. When it is impossible to change route or travel time e.g. due to personal restraints, or when simply no other transport mode is available, women are captives to use unwanted transport options, even when they have to reckon with frightening situations. The conclusions summarize that women’s personal security plays an important role in terms of travel behaviour and increased attention should be paid by authorities as well as city- and transport planners striving for sustainable built environments. As the share of affected women is high and it can be assumed that women are more often imperilled than men the questions arises, if this can be assimilated to unequal mobility opportunities, finally resulting in a social deficiency for women.     

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male’s emotion dynamics over time, but not in the female’s—which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.     

A Bayesian-optimal principle for learner-friendly adaptation in learning games

Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predictable and thus uninformative. Still, tasks that are efficient for learning may be experienced as too challenging, and the resulting failures can lower motivation. Therefore, in addition to quantifying the expected informational benefit for learning of any prospective task to be presented next, we also model the expected motivational cost of its presentation, measured simply as the estimated probability of failure in our example model. We propose a “learner-friendly” adaptation algorithm that chooses the learning tasks by optimizing the expected benefit divided by the expected cost. We apply this algorithm to a Rasch-like student model implemented within a real-world application and present initial results of a pilot experiment.     

Specificity of Task Constraints and Effects of Visual Demonstrations and Verbal Instructions in Directing Learners' Search During Skill Acquisition

In the present study, the efficacy of visual demonstrations and verbal instructions as instructional constraints on the acquisition of movement coordination was investigated. Fifteen participants performed an aiming task on 100 acquisition and 20 retention trials, under 1 of 3 conditions: a modeling group (MG), a verbally directed group (VDG), and a control group (CG). The MG observed a model intermittently throughout acquisition, whereas the VDG was verbally instructed to use the model's movement pattern. Participants in the CG received neither form of instruction. Kinematic analysis revealed that compared with verbal instructions or no instructions, visual demonstrations significantly improved participants' approximation of the model's coordination pattern. No differences were found in movement outcomes. Coordination data supported the visual perception perspective on observational learning, whereas outcome data suggested that the modeling effect is mainly a function of task constraints, that is, the novelty of a movement pattern.