PROVIDING GLOBAL PUBLIC GOODS: ELECTORAL DELEGATION AND COOPERATION

This study experimentally examines the effect of electoral delegation on providing global public goods shared by several groups. Each group elects one delegate who can freely decide on each group member's contribution to the global public goods. Our results show that people mostly vote for delegates who assign equal contributions for every group member. However, in contrast to standard theoretical predictions for our delegation mechanism, unequal contributions across groups drive cooperation down over time, and it decreases efficiency by almost 50% compared to the selfish benchmark. This pattern is not driven by delegates trying to exploit their fellow group members, as indicated by theory. It is driven by conditional cooperation of delegates across groups. Since one of the potential sources of the resulting inefficiency is the polycentric nature of global public goods provision together with other‐regarding preferences, we use the term P‐inefficiency to describe our finding. (JEL C92, D72, H41)     

Temporal Responsiveness in Mother–Child Dialogue: A Longitudinal Analysis of Children with Normal Hearing and Hearing Loss

Dialogue between conversational partners, including mothers and their children, is precisely timed. The predictability of this timing is important for establishing and maintaining interaction, communication, and learning. This longitudinal study examines changes in the response latency of utterances in dialogue between mothers and their normal hearing and hearing‐impaired children between 4 and 60 months of age. Mothers and their children showed parallel developmental trends, responding to each other more quickly at older ages. Beyond these age‐related group effects, significant dyadic effects were found in which individual children's latencies were related to those of their mothers, and vice versa. Developmental patterns did not significantly differ across hearing status groups, which may reflect the role of early identification and intervention in promoting positive developmental outcomes.     

Overcoming the ‘tyranny of the urgent’: integrating gender into disease outbreak preparedness and response

ABSTRACT

This article contributes to discussions on the gender dimensions of disease outbreaks, and preparedness policies and responses, by providing a multi-level analysis of gender-related gaps, particularly illustrating how the failure to challenge gender assumptions and incorporate gender as a priority at the global level has national and local impacts. The implications of neglecting gender dynamics, as well as the potential of equity-based approaches to disease outbreak responses, is illustrated through a case study of the Social Enterprise Network for Development (SEND) Sierra Leone, a non-government organisation (NGO) based in Kailahun, during the Ebola outbreak.     

Measuring stakeholder identification with nonprofit causes: the development and validation of the identification with social causes scale

Nonprofit organizations (NPOs) achieve desired outcomes by fostering organizational identification. However, little research has explored how identification with the cause or the recipients of support relates to identification with the NPO. This study developed the Identification with Social Causes Scale as a mechanism for distinguishing organizational identification from identification with a social group or cause. Data were collected using two groups: the homeless (n = 318) and HIV positive (n = 314) individuals. Exploratory factor analysis and multigroup confirmatory factor analysis yielded a 9-item scale measuring two dimensions: attachment and consubstantiality. Initial construct validity of the scale was established.     

Load-Oriented Order Release (LOOR) revisited: bringing it back to the state of the art

In the workload control literature, the Load-Oriented Order Release (LOOR) approach has been neglected since its robustness was questioned at the end of the 1990s. This paper revisits LOOR and evaluates whether its performance can be improved in two ways. First, an intermediate pull release mechanism is added to avoid starvation between periodic release events. This mechanism was recently shown to be effective at improving the performance of a state-of-the-art release method known as LUMS COR. Second, an integer linear programming model is used to manage the trade-off between the timing and load balancing functions of order release. The two refinements are assessed using simulations of different shop configurations, which allow us to evaluate robustness. Results demonstrate that the refinements contribute to improving the performance of LOOR such that it can even outperform LUMS COR. Perhaps counter-intuitively, putting more emphasis on load balancing than on the urgency of individual orders is shown to lead to a lower percentage of tardy orders. Overall, the improvements mean that concerns about LOOR’s robustness are no longer valid – it now appears suitable for a wide range of shops found in practice.     

Learning discrete decomposable graphical models via constraint optimization

Statistical model learning problems are traditionally solved using either heuristic greedy optimization or stochastic simulation, such as Markov chain Monte Carlo or simulated annealing. Recently, there has been an increasing interest in the use of combinatorial search methods, including those based on computational logic. Some of these methods are particularly attractive since they can also be successful in proving the global optimality of solutions, in contrast to stochastic algorithms that only guarantee optimality at the limit. Here we improve and generalize a recently introduced constraint-based method for learning undirected graphical models. The new method combines perfect elimination orderings with various strategies for solution pruning and offers a dramatic improvement both in terms of time and memory complexity. We also show that the method is capable of efficiently handling a more general class of models, called stratified/labeled graphical models, which have an astronomically larger model space.     

Does race matter? Assessing consumer discrimination in the secondary basketball card market

Sociologists continue to observe the ways race permeates America's social institutions, the institution of sport being no exception. Although researchers have explored customer racial discrimination via examinations of the secondary sports card market, only three studies have explored the phenomenon in the context of basketball, a sporting context with a higher proportion of non-White players than the baseball and football leagues that have been the primary focus to date. We explore the unique way race matters on the hardwood by employing a methodological approach that previously has been used to study card collecting in other contexts. Data were obtained for 215 retired players and their rookie cards. Controlling for other factors, to include career performance, position, and card scarcity, the results reveal no direct effect of race on card values, but there is an interaction effect between race and Hall of Fame status that impacts card prices. The potential source and implications of this interaction are discussed as well as suggestions for future research.