Quantitative Storytelling in the Making of a Composite Indicator

The reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures—which ultimately aim to ‘tell a story’, e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction. We thus explore whether a composite indicator can be built to tell ‘more than one story’ and test this in practical contexts. These include measures used in convergence analysis in the field of cohesion policies and a recent case involving the World Bank’s Doing Business Index. Our experiments are built to imagine different constituencies and stakeholders who agree on the use of evidence and of statistical information while differing on the interpretation of what is relevant and vital.

     

Opting out of workers’ compensation: Non-subscription in Texas and its effects

Journal of Risk and Uncertainty - Texas is the only state that does not mandate that employers carry workers’ compensation (WC) insurance coverage. In place of traditional WC, companies can...     

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.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

‘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.     

Business Collaboration within the Nazi War Machine: Corporations and the State in the Austrian Semiperiphery

The military strength of German National Socialism was based on the collaboration of large corporations with the Nazi state. Business provided capital, loans, taxes, managerial expertise and production for war industries. I elaborate four ideal‐typical modes of business collaboration. Each mode is illustrated by a case study of a German corporation that acquires an Austrian firm: Krupp (traditional mode); the Reichswerke state conglomerate (coercive); Deutsche Bank (managerial nationalist); and IG Farben (competitive investment mode). The first and the last modes occurred when the state was highly dependent on large businesses for the economic requisites of war. The acquired firms in the Austrian semiperiphery contributed to Nazi war mobilization, as they exploited labor and resources from the peripheral regions of southeastern Europe. Patterns of the state's resource dependency on business led to bargaining interactions between state and business, over time shaping the mix between state and private ownership of war industry.     

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.     

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.     

Child learning and family mealtime environment,parenting style and family functioning among preschoolers in Hong Kong

A two-wave longitudinal study on 470 parent–child dyads examined the impact of family mealtime environment, parenting style and family functioning on preschoolers’ (three to six years old) learning. Measures included parent report on parenting style, family functioning, family meal frequency, mealtime television, feeding practice, teacher/parent report of academic competence and individual assessment of preschoolers’ preschool concepts. Family mealtime environment variables were associated with pre-schoolers’ learning, in addition to parenting style and family functioning, after controlling for family income and wave 1 preschoolers’ learning. The results highlighted the importance of family mealtime environment on preschoolers’ learning.