Benevolence-dominant,authoritarianism-dominant,and classical paternalistic leadership: Testing their relationships with subordinate performance

We propose a new typology of paternalistic leadership styles based on how leaders demonstrate authoritarianism and benevolence, the two essential components of this type of leadership. Benevolence-dominant paternalistic leadership refers to leaders' sole dependence on the use of benevolence without their strong assertion of authority, whereas authoritarianism-dominant paternalistic leadership is based mainly on authoritarianism itself; classical paternalistic leadership, which best fits early observations of paternalistic leaders, refers to the salient combination of both leadership components. We used two distinct samples and methods to test this typology and the association with subordinate performance. Across the two studies, a field investigation with Taiwanese military supervisor-subordinate dyads and a hypothetical scenario experiment with U.S. working adults, we found a positive relationship between classical paternalistic leadership and subordinate performance as strong as that between benevolence-dominant paternalistic leadership and performance. Our findings echo the phenomenon that paternalistic leaders tend to combine benevolence with authoritarianism to affect subordinate performance.     

Bayesian networks for imputation

Summary.  Bayesian networks are particularly useful for dealing with high dimensional statistical problems. They allow a reduction in the complexity of the phenomenon under study by representing joint relationships between a set of variables through conditional relationships between subsets of these variables. Following Thibaudeau and Winkler we use Bayesian networks for imputing missing values. This method is introduced to deal with the problem of the consistency of imputed values: preservation of statistical relationships between variables ( statistical consistency ) and preservation of logical constraints in data ( logical consistency ). We perform some experiments on a subset of anonymous individual records from the 1991 UK population census.     

Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467–475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters’ prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters’ prior beliefs.     

‘More like a daughter than an employee’: the kinning process between migrant care workers,elderly care receivers and their extended families

ABSTRACT

This paper explores the intersections of formal and informal care in the relationships that develop between elderly care receivers and their families and migrant domestic care workers and their families. The domestic migrant care literature has tended to focus on two main ‘hidden costs’ of this ‘care-chain’: the ‘care exploitation’ of paid carers by their employers and the ‘care drain’ impact on the family members left behind by the migrant. In this paper, we employ a care circulation framework to examine the process of becoming kin-like – or ‘kinning’, which remains relatively under-explored and warrants further research. An analysis of this process of kinning helps to highlight how the domestic space of care receiver homes are transformed – through the negotiation of relationships with migrant care workers – into transnational social fields that bring the diaspora worlds of the migrants into the everyday worlds of the locals.     

Enabling robust assessment of QTc prolongation in early phase clinical trials

Since the implementation of the International Conference on Harmonization (ICH) E14 guideline in 2005, regulators have required a “thorough QTc” (TQT) study for evaluating the effects of investigational drugs on delayed cardiac repolarization as manifested by a prolonged QTc interval. However, TQT studies have increasingly been viewed unfavorably because of their low cost effectiveness. Several researchers have noted that a robust drug concentration‐QTc (conc‐QTc) modeling assessment in early phase development should, in most cases, obviate the need for a subsequent TQT study. In December 2015, ICH released an “E14 Q&As (R3)” document supporting the use of conc‐QTc modeling for regulatory decisions. In this article, we propose a simple improvement of two popular conc‐QTc assessment methods for typical first‐in‐human crossover‐like single ascending dose clinical pharmacology trials. The improvement is achieved, in part, by leveraging routinely encountered (and expected) intrasubject correlation patterns encountered in such trials. A real example involving a single ascending dose and corresponding TQT trial, along with results from a simulation study, illustrate the strong performance of the proposed method. The improved conc‐QTc assessment will further enable highly reliable go/no‐go decisions in early phase clinical development and deliver results that support subsequent TQT study waivers by regulators.     

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

Lessons from Nigeria for improved thinking and working politically in the extractives sector

Despite the wealth that comes from being the biggest oil producer in Africa, Nigeria has some of the worst development indicators in the world. From 2011 to mid‐2016, the DFID‐funded Facility for Oil Sector Transparency and Reform (FOSTER) programme's unique design aimed to reduce incentives for the capture of oil revenue by elites and international oil companies, restoring the potential of those revenues to accelerate economic and social development. This article asks what lessons FOSTER's successes and failures offer for improved “thinking and working politically” (TWP). It examines the outcomes from five “clusters” of interventions: three viewed by the FOSTER team as successes and two as failures. The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The research used a qualitative and inductive approach. Field research was undertaken with 44 semi‐structured qualitative interviews during one month of fieldwork in Abuja and Lagos. The research also included reviews of FOSTER's internal documentation and evaluation frameworks, as well as analysis of newspaper articles and grey literature on the oil sector in Nigeria. The project offers important lessons for politically informed programming about how interventions were implemented (process), what was actually done (content) and how the project responded to changes in context that created or blocked opportunities for reform (responsiveness). The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The findings have important implications for programme design. They demonstrate the value of built‐in flexibility that allows staff to choose and switch the partners they work with and the channels they work through. They also show that a key aspect of TWP‐based programming is implicit acceptance that some failure may be unavoidable, since this permits staff to balance risk against opportunities. Finally, a better understanding of FOSTER's failures reveals the challenges of a TWP‐based approach and the trade‐offs it demands.