Why global justice matters

Why does global justice as a philosophical inquiry matter? We know that the world is plainly unjust in many ways and we know that something ought to be done about this without, it seems, the need of a theory of global justice. Accordingly, philosophical inquiry into global justice comes across to some as an intellectual luxury that seems disconnected from the real world. I want to suggest, however, that philosophical inquiry into global justice is necessary if we want to address the problems of humanity. First, in some cases, a theory of global justice is needed for identifying what counts as legitimate problems of justice. Second, even in obvious cases of injustices, such as the fact of preventable extreme poverty to which we know we have an obligation to respond, we cannot know the content and the limits of these obligations and who the primary bearers of these obligations are without some theoretical guidance. However, I acknowledge that philosophical inquiry on global justice risks becoming a philosophical parlor game if it loses sight of the real-world problems that motivate the inquiry in the first place. If global justice is to provide the tools for addressing the problems of humanity, it must remain a problems-driven enterprise.     

Global ethics: increasing our positive impact

Global ethics is no ordinary subject. It includes some of the most urgent and momentous issues the world faces, such as extreme poverty and climate change. Given this, any adequate review of that subject should, I suggest, ask some questions about the relation between what those working in that subject do and the real-world phenomena that are the object of their study. The main question I focus on in this essay is this: should academics and others working in the field of global ethics take new measures aimed at having more real-world positive impact on the phenomena they study? Should they take new measures, that is, aimed at bringing about more improvements in those phenomena, improvements such as reductions in extreme poverty and in emissions of greenhouse gases? I defend a positive answer to this question against some objections, and also discuss some of the kinds of measure we might take in an attempt to have more positive impact.     

Eyewitness identification discriminability: ROC analysis versus logistic regression

To reach conclusions regarding the respective accuracy of two conditions, eyewitness researchers evaluate correct and false identification rates computed across participants. Two approaches typically are employed. One approach relies on ratio-based probative value measures; but Wixted and Mickes (2012) and Gronlund, Wixted, and Mickes (2014) showed that these measures fail to disentangle an assessment of accuracy (i.e., discriminability between guilty and innocent suspects) from response bias (i.e., a willingness to make a response). Our focus is on a second approach, logistic regression analyses of the correct and of the false identification rates. Logistic regression also fails to disentangle discriminability from bias. Therefore, it only can denote the most accurate condition in limited circumstances. The best approach for reaching the proper conclusion regarding which condition is most accurate is to use receiver operator characteristic (ROC) analysis. Simulated ROC data illustrate the problem with a reliance on logistic regression to assess accuracy.     

Introduction: education and migration

ABSTRACT

This introduction expounds educational problems that arise from transnational migration. It argues that it is high time to critically analyze normative issues of and in education under conditions of globalization because dominant approaches in normative philosophy of education tend to suffer from both a nationalist bias and a sedentary bias. The contributions to this special issue address normative problems pertaining to migration-related education from a variety of ethical and philosophical perspectives, including analytic applied ethics, continental philosophy, care ethics, Hegelian philosophy, the capability approach and theories of distributive justice. They discuss the education of both citizens and migrants in the receiving society as well as in the country of origin, focusing on ethical issues pertaining to access to education as well as to the content of educational programs.     

CAN SCIENCE AND RELIGION RESPOND TO CLIMATE CHANGE?

With the challenge of communicating climate science in the United States and making progress in international negotiations on climate change there is a need for other approaches. The moral issues of ecological degradation and climate justice need to be integrated into social consciousness, political legislation, and climate treaties. Both science and religion can contribute to this integration with differentiated language but shared purpose. Recognizing the limits of both science and religion is critical to finding a way forward for addressing the critical challenges of climate change. How we value nature and human–Earth relations is crucial to this. We need a broader environmental ethics in dialogue with the science of climate change.     

Modeling response signal and response time data

The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of experimenter-determined times, a signal to respond is presented. The models were fit to the data from the two procedures simultaneously under the assumption that responses in the response signal procedure were based on a mixture of decision processes that had already terminated at response boundaries before the signal and decision processes that had not yet terminated. In the latter case, decisions were based on partial information in one variant of each model or on guessing in a second variant. Both variants of the diffusion model fit the data well and both fit better than either variant of the LCA model, although the differences in numerical goodness-of-fit measures were not large enough to allow decisive selection between the models.     

Stimulus disparity and punisher control of human signal-detection performance

The present experiment examined the effects of varying stimulus disparity and relative punisher frequencies on signal detection by humans. Participants were placed into one of two groups. Group 3 participants were presented with 1:3 and 3:1 punisher frequency ratios, while Group 11 participants were presented with 1:11 and 11:1 punisher frequency ratios. For both groups, stimulus disparity was varied across three levels (low, medium, high) for each punisher ratio. In all conditions, correct responses were intermittently reinforced (1:1 reinforcer frequency ratio). Participants were mostly biased away from the more punished alternative, with more extreme response biases found for Group 11 participants compared to Group 3. For both groups, estimates of discriminability increased systematically across the three disparity levels and were unaffected by the punisher ratios. Likewise, estimates of response bias and sensitivity to the punisher ratios were unaffected by changes in discriminability, supporting the assumption of parameter invariance in the Davison and Tustin (1978) model of signal detection. Overall, the present experiment found no relation between stimulus control and punisher control, and provided further evidence for similar but opposite effects of punishers to reinforcers in signal-detection procedures.     

Underlying correlation structures of parental stress, general health and anxiety

A partial least square regression (PLSR) was performed on the Swedish Parenthood Stress Questionnaire (SPSQ) sum score and subscales on incompetence, role restriction, social isolation, spouse relationship and health problems, using 42 items from the General Health Questionnaire (GHQ) and 20 items from the State Anxiety Inventory (STAI-X1). The dataset contained 227 fathers and 301 mothers of children aged 1.0-6.6 years from a population-based study on parental psychological distress in the general Norwegian population, and all items correlated positively with SPSQ. Subscales on spouse relationship, incompetence, social isolation and role restriction related to items on state anxiety and depression. The SPSQ subscale on health problems related to GHQ items on somatic symptoms and social dysfunction. The STAI-X1 item "not feeling rested" had a particularly important effect on parental stress. Underlying correlation structures between parental stress and items from STAI-X1 and GHQ were explored, but only the SPSQ sum score could be acceptably predicted. PLSR as a statistical methodology was found useful for health and psychometric data.     

A Signal Detection Model for Multiple-Choice Exams

A model for multiple-choice exams is developed from a signal-detection perspective. A correct alternative in a multiple-choice exam can be viewed as being a signal embedded in noise (incorrect alternatives). Examinees are assumed to have perceptions of the plausibility of each alternative, and the decision process is to choose the most plausible alternative. It is also assumed that each examinee either knows or does not know each item. These assumptions together lead to a signal detection choice model for multiple-choice exams. The model can be viewed, statistically, as a mixture extension, with random mixing, of the traditional choice model, or similarly, as a grade-of-membership extension. A version of the model with extreme value distributions is developed, in which case the model simplifies to a mixture multinomial logit model with random mixing. The approach is shown to offer measures of item discrimination and difficulty, along with information about the relative plausibility of each of the alternatives. The model, parameters, and measures derived from the parameters are compared to those obtained with several commonly used item response theory models. An application of the model to an educational data set is presented.