From Zero to Hero? An analysis of the human rights protections within the Global Compact for Safe,Orderly and Regular Migration (GCM)

This article examines the Global Compact for Safe, Orderly and Regular Migration (GCM) from three perspectives: First, while the GCM is not legally binding, the human rights obligations of states which underpin the GCM are. The application of international human rights law to everyone, including migrants, has led to frictions in the inter‐governmental negotiation process, with some states declining to sign the GCM. States cannot relieve themselves of the human rights obligations to which they are already, voluntarily, bound by refusing to sign the GCM. Second, the GCM asserts the human rights of migrants, and by implication condemns state practices contrary thereto, but it also yields to political sensitivities. Thus, we encounter a Compact that defends existing human rights standards, but concurrently submits to political will and tolerates conditions of vulnerability. Third, the GCM’s implementation depends upon, as yet undefined, partnerships with non‐State actors and monitoring against human rights standards.     

Assessment of Patient Classification in Appointment System Design

This paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and appointment interval adjustment. In the latter approach, appointment intervals are adjusted to match the consultation time characteristics of different patient classes. Our simulation results indicate that new appointment systems that utilize interval adjustment for patient class are successful in improving doctors' idle time, doctors' overtime and patients' waiting times without any trade‐offs. Best performing appointment systems are identified for different clinic environments characterized by walk‐ins, no‐shows, the percentage of new patients, and the ratio of the mean consultation time of new patients to the mean consultation time of return patients. As a result, practical guidelines are developed for managers who are responsible for designing appointment systems.     

A Universal Appointment Rule in the Presence of No‐Shows and Walk‐Ins

This study introduces a universal “Dome” appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factors—no‐shows, walk‐ins, number of appointments per session, variability of service times, and cost of doctor's time to patients’ time. Simulation and nonlinear regression are used to derive an equation to predict the planning constant as a function of the environmental factors. We also introduce an adjustment procedure for appointment systems to explicitly minimize the disruptive effects of no‐shows and walk‐ins. The procedure adjusts the mean and standard deviation of service times based on the expected probabilities of no‐shows and walk‐ins for a given target number of patients to be served, and it is thus relevant for any appointment rule that uses the mean and standard deviation of service times to construct an appointment schedule. The results show that our Dome rule with the adjustment procedure performs better than the traditional rules in the literature, with a lower total system cost calculated as a weighted sum of patients’ waiting time, doctor's idle time, and doctor's overtime. An open‐source decision‐support tool is also provided so that healthcare managers can easily develop appointment schedules for their clinical environment.     

Day-of-the-Week Effects in Subjective Well-Being: Does Selectivity Matter?

Individuals tend to self-report higher well-being levels on certain days of the week than they do on the remaining days, controlling for observables. Using the 2008 release of the British Household Panel Survey, we test whether this empirical observation suffers from selection bias. In other words, we examine if subjective well-being is correlated with unobserved characteristics that lead the individuals to take the interview on specific days of the week. We focus on two distinct well-being measures: job satisfaction and happiness. We provide convincing evidence for both of these measures that the interviews are not randomly distributed across the days of the week. In other words, individuals with certain unobserved characteristics tend to take the interviews selectively. We conclude that a considerable part of the day-of-the-week patterns can be explained by a standard “non-random sorting on unobservables” argument rather than “mood fluctuations”. This means that the day-of-the-week estimates reported in the literature are likely to be biased and should be treated cautiously.     

Performances of some goodness-of-fit tests for sampling designs in ranked set sampling

In this study, we consider different sampling designs of ranked set sampling (RSS) and give empirical distribution function (EDF) estimators for each sampling designs. We provide comparative graphs for the EDFs. Using these EDFs, power of five goodness-of-fit tests are obtained by Monte Carlo simulations for Tukey's g–h distributions under RSS and simple random sampling (SRS). Performances of these tests are compared with the tests based on the SRS. Also, critical values belong to these tests are obtained for different set and cycle sizes.     

Home Ownership and Job Satisfaction

This paper investigates the link between job satisfaction and home ownership. We explicitly focus on the effect of a transition from non-ownership to ownership on the self-reported job satisfaction scores. In other words, we concentrate on the change in job satisfaction response for individuals observed right before and after the transition. Utilizing the panel feature of the British Household Panel Survey, we find that transition to ownership reduces job satisfaction within a year following the purchase—controlling for observed variation and unobserved heterogeneity. The reduction in job satisfaction is sharper when the purchase is financed through a mortgage. We also test if this pattern persists over years. We show that the initial reduction in job satisfaction is more than doubled within 3 years after the transition for both categories of ownership. We conclude that home ownership may be a constraint for the career prospects of the employed workers, since it reduces mobility and forces them to become more dependent on the local labor market conditions. These concerns are deeper in case of a debt-financed ownership.     

Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts

High levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, but the exact nature of the dose-response relationship is less well understood. To investigate this relationship, data were assembled from six longitudinal birth cohort studies examining the effects of PAE on cognitive outcomes from early school age through adolescence. Structural equation models (SEMs) are a natural approach to consider, because of the way they conceptualise multiple observed outcomes as relating to an underlying latent variable of interest, which can then be modelled as a function of exposure and other predictors of interest. However, conventional SEMs could not be fitted in this context because slightly different outcome measures were used in the six studies. In this paper we propose a multi-group Bayesian SEM that maps the unobserved cognition variable to a broad range of observed outcomes. The relation between these variables and PAE is then examined while controlling for potential confounders via propensity score adjustment. By examining different possible dose-response functions, the proposed framework is used to investigate whether there is a threshold PAE level that results in minimal cognitive deficit.