Compliance Versus Risk in Assessing Occupational Exposures

Assessments of occupational exposures to chemicals are generally based upon the practice of compliance testing in which the probability of compliance is related to the exceedance [γ, the likelihood that any measurement would exceed an occupational exposure limit (OEL)] and the number of measurements obtained. On the other hand, workers’ chronic health risks generally depend upon cumulative lifetime exposures which are not directly related to the probability of compliance. In this paper we define the probability of “overexposure” (θ) as the likelihood that individual risk (a function of cumulative exposure) exceeds the risk inherent in the OEL (a function of the OEL and duration of exposure). We regard θ as a relevant measure of individual risk for chemicals, such as carcinogens, which produce chronic effects after long-term exposures but not necessarily for acutely-toxic substances which can produce effects relatively quickly. We apply a random-effects model to data from 179 groups of workers, exposed to a variety of chemical agents, and obtain parameter estimates for the group mean exposure and the within- and between-worker components of variance. These estimates are then combined with OELs to generate estimates of γ and θ. We show that compliance testing can significantly underestimate the health risk when sample sizes are small. That is, there can be large probabilities of compliance with typical sample sizes, despite the fact that large proportions of the working population have individual risks greater than the risk inherent in the OEL. We demonstrate further that, because the relationship between θ and γ depends upon the within- and between-worker components of variance, it cannot be assumed a priori that exceedance is a conservative surrogate for overexposure. Thus, we conclude that assessment practices which focus upon either compliance or exceedance are problematic and recommend that employers evaluate exposures relative to the probabilities of overexposure.     

Importance of interpolation when constructing double-bootstrap confidence intervals

We show that, in the context of double-bootstrap confidence intervals, linear interpolation at the second level of the double bootstrap can reduce the simulation error component of coverage error by an order of magnitude. Intervals that are indistinguishable in terms of coverage error with theoretical, infinite simulation, double-bootstrap confidence intervals may be obtained at substantially less computational expense than by using the standard Monte Carlo approximation method. The intervals retain the simplicity of uniform bootstrap sampling and require no special analysis or computational techniques. Interpolation at the first level of the double bootstrap is shown to have a relatively minor effect on the simulation error.     

GMM Estimation with persistent panel data: an application to production functions

This paper considers the estimation of Cobb-Douglas production functions using panel data covering a large sample of companies observed for a small number of time periods. GMM estimatorshave been found to produce large finite-sample biases when using the standard first-differenced estimator. These biases can be dramatically reduced by exploiting reasonable stationarity restrictions on the initial conditions process. Using data for a panel of R&Dperforming US manufacturing companies we find that the additional instruments used in our extended GMM estimator yield much more reasonable parameter estimates.     

The Quality of Urban Environments in the Brazilian Amazon

In the Brazilian Amazon during the 1980s,urban population growth outstripped rural growth, andby 1991, most of the region's population resided inurban areas. Much of this urban growth involvedestablishment of unplanned housing with inadequateinfrastructure, which resulted in rising pollution. This paper compares indicators of environmentalquality in urban populations of the Amazon in 1980 and1991, and among different kinds of urban populationsin 1991. The results show that environmental qualityin the region deteriorated during the 1980s as theproduction of and exposure to environmental hazardsrose while resources to ward off hazards eroded. Thefindings also show that environmental quality wasparticularly poor in more rapidly growing urbancenters. The urban Amazon may not afford an adequatestandard of living and this may generate out-migrationfrom the region.     

DETERMINING THE APPROPRIATE DISCOUNT RATES IN PURE CAPITAL RATIONING

This paper proposes an interpretation of the pure capital rationing problem as it is faced by many managers in decentralized firms in which budgets serve as the principal means of control. It is argued that the appropriate objective for situations such as these is the maximization of either undiscounted earnings over the planning horizon or total value of the investments at the horizon. When either objective function is used in conjunction with the frequently encountered linear programming models for the capital rationing problem, shadow prices result which give rise to discount rates that will reproduce the optimal solution using discounted cash flow as a criterion. These results are then used as a means for clarifying several confusing and misleading statements that have appeared in the literature.     

Screens in bed: visual art,sleep and handheld screen devices

This article seeks an understanding of sleeping and waking life in bed in relation to the use of handheld screen devices. The bedtime use of these devices has come to public attention through the involvement of this practice in the construction of two contemporary crises of sleep: Sleep science’s crisis of chronic sleep deprivation and the wider cultural crisis of the invasion of sleep by fast capitalism, as proposed by Jonathan Crary. Visual art is employed to gain insights into the two related understandings of sleep: one concerned with individual sleep self-regulation and the other with the corporeal commonality of sleep. The sociology of sleep, based on Michele Foucault’s concept of ‘biopower’, is augmented by philosophical insights from Jean-Luc Nancy and Gilles Deleuze to reconfigure the sleeping body beyond the bounds of disciplinary regimes and permit a reassessment of the affective potential of sleep. Works of digital media art, together with ethnographic and cultural studies on the use of mobile devices, are employed to tease out the entanglement of these screen devices with waking and sleeping bedroom life. An ontology of sleep as a pre-individual affective state is proposed as an alternative basis for resisting the appropriation of sleep by the always-waking world accessed through the use of smartphones and tablets.     

在公共服务递送中运营共同生产：服务蓝图的贡献

本文认为,公共服务应从以产品为主导的逻辑转向服务途径。通过采取服务导向,公共服务递送的经验性、组织间和系统性,以及作为共同生产者的服务使用者角色,将一同被考虑。论文将通过服务蓝图的应用,解释共同生产如何操作。并介绍了高等教育中的一个案例。在这一案例中,蓝图的创建将师生汇聚在一起,专注于学生入学的设计,从而改善学生体验,并支持共同生产。      

Stochastically optimal bootstrap sample size for shrinkage-type statistics

In nonregular problems where the conventional \(n\) out of \(n\) bootstrap is inconsistent, the \(m\) out of \(n\) bootstrap provides a useful remedy to restore consistency. Conventionally, optimal choice of the bootstrap sample size \(m\) is taken to be the minimiser of a frequentist error measure, estimation of which has posed a major difficulty hindering practical application of the \(m\) out of \(n\) bootstrap method. Relatively little attention has been paid to a stronger, stochastic, version of the optimal bootstrap sample size, defined as the minimiser of an error measure calculated directly from the observed sample. Motivated by this stronger notion of optimality, we develop procedures for calculating the stochastically optimal value of \(m\). Our procedures are shown to work under special forms of Edgeworth-type expansions which are typically satisfied by statistics of the shrinkage type. Theoretical and empirical properties of our methods are illustrated with three examples, namely the James–Stein estimator, the ridge regression estimator and the post-model-selection regression estimator.     

Differences by gender, ethnicity, and acculturation in the efficacy of the keepin' it REAL model prevention program

This study examined whether the efficacy of keepin' it REAL, a model program for substance use prevention in schools, was moderated by gender, ethnicity, and acculturation. Gender differences in program efficacy may arise through boys' higher risk of drug use, inadequate attention to girls' developmental issues, or cultural factors like polarized gender expectations. Data came from a randomized trial in 35 Phoenix, Arizona, middle schools involving 4,622 mostly Latino 7th graders. Using multi-level mixed models and multiple imputation missing techniques, results for the total sample showed no gender differences in program effects on recent substance use, but the program was more effective in fostering boys' than girls' anti-drug norms. Subgroup analyses demonstrated several more beneficial program effects for boys than girls (less alcohol and cigarette use and stronger anti-drug norms), but only among less acculturated Latinos. There were no gender differences in program effects among more acculturated Latinos, nor among non-Latino whites.