Ecological Risks of Diazinon from Agricultural Use in the Sacramento – San Joaquin River Basins, California

A probabilistic risk assessment was conducted to evaluate the likelihood and ecological significance of potential toxic effects of diazinon in the Sacramento-San Joaquin system. Diazinon, an organophosphorus insecticide, is used in the Sacramento-San Joaquin River Basin as a dormant spray on almonds and other tree crops, as well as for other agricultural and urban applications. Diazinon and other pesticides have been detected in the Sacramento and San Joaquin Rivers and their tributaries. Diazinon exposure was characterized based on monitoring programs conducted in 1991-94. Diazinon effects were characterized using laboratory toxicity data for 63 species, supplemented by results from field mesocosm and microcosm studies. The assessment addressed the possibility that reductions in invertebrate populations could lead to impacts on species of fish that feed on those invertebrates. The risk assessment concluded that fish in these rivers are not at risk from the direct effects of diazinon in the water. Invertebrates are at greater risk, especially in agriculturally dominated streams and drainage channels during January and February. Cladocerans--including Daphnia magna and Ceriodaphnia dubia, two common bioassay species--are especially sensitive to diazinon and other organophosphates and are likely to be subject to acute toxic effects in some locations at some times. Any ecological damage that may occur, however, is brief and limited to cladocerans. None of the fish species of concern depend on cladocerans as critical components of their diet. Invertebrates that are not affected by observed concentrations of diazinon (copepods, mysids, amphipods, rotifers, and insects) are preferred foods for fish in the Sacramento-San Joaquin system.     

Overcoming Confirmation Bias in Causal Attribution: A Case Study of Antibiotic Resistance Risks

When they do not use formal quantitative risk assessment methods, many scientists (like other people) make mistakes and exhibit biases in reasoning about causation, if‐then relations, and evidence. Decision‐related conclusions or causal explanations are reached prematurely based on narrative plausibility rather than adequate factual evidence. Then, confirming evidence is sought and emphasized, but disconfirming evidence is ignored or discounted. This tendency has serious implications for health‐related public policy discussions and decisions. We provide examples occurring in antimicrobial health risk assessments, including a case study of a recently reported positive relation between virginiamycin (VM) use in poultry and risk of resistance to VM‐like (streptogramin) antibiotics in humans. This finding has been used to argue that poultry consumption causes increased resistance risks, that serious health impacts may result, and therefore use of VM in poultry should be restricted. However, the original study compared healthy vegetarians to hospitalized poultry consumers. Our examination of the same data using conditional independence tests for potential causality reveals that poultry consumption acted as a surrogate for hospitalization in this study. After accounting for current hospitalization status, no evidence remains supporting a causal relationship between poultry consumption and increased streptogramin resistance. This example emphasizes both the importance and the practical possibility of analyzing and presenting quantitative risk information using data analysis techniques (such as Bayesian model averaging (BMA) and conditional independence tests) that are as free as possible from potential selection, confirmation, and modeling biases.     

Serpents in the Sand: Managerial Networking and Nonlinear Influences on Organizational Performance

Scholars of public management have consistently found that managementmatters, but little research has considered how much managementmatters or whether the link between management and performancemay be contingent on various factors. This article further investigatesthe link between management and performance by examining thefunctional form of the relationship. Analyses using data from1000+ public organizations point to some diminishing returns.Results suggest that networking with other organizations mightnot always result in gains for the organization. Findings alsoshow how managerial quality and differences in organizationalstaff can affect this relationship.     

Outcomes assessment: evaluation in routine practice

Evaluating the quality and effectiveness of human services, whether social services or medical services, is critically important for the providers, for the organization, and for the payers of those services. We propose that outcomes assessment, a continuous model of evaluation designed for routine services settings, can be considered for use in evaluating the effectiveness of human services on a routine basis. In medical care, outcomes assessment measures initial and subsequent disorder-specific and generic outcomes domains as well as prognostic or case-mix characteristics that can be used to adjust outcomes among groups. We describe a current implementation of outcomes assessment in a state mental health system in the US and make recommendations for the future of the field.     

Some Limitations of “Risk = Threat × Vulnerability × Consequence” for Risk Analysis of Terrorist Attacks

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk=Threat×Vulnerability×Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP?) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk‐scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two‐level (or few‐level) hierarchical optimization models can provide a useful alternative to Risk=Threat×Vulnerability×Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two‐level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.     

史公和时势——论《史记》对武帝时政的委曲批评

以前的学者谈司马迁的思想时,比较喜欢提出他对儒家和黄老的意见。本文则重点考察司马迁怎样通过多样化的撰写技巧,表明自己对于汉武帝时政的评价,指出司马迁既反对武帝对匈奴的战争,也反对武帝任用酷吏。他所采取的是一种委曲批评的方式,即所谓"继《春秋》"之"忌讳之辞"。     

Does the supplemental nutrition assistance program really increase obesity? The importance of accounting for misclassification errors

The prevalence of obesity among US citizens has grown rapidly over the last few decades, especially among low-income individuals. This has led to questions about the effectiveness of nutritional assistance programs such as the Supplemental Nutrition Assistance Program (SNAP). Previous results on the effect of SNAP participation on obesity are mixed. These findings are however based on the assumption that participation status can be accurately observed, despite significant misclassification errors reported in the literature. Using propensity score matching, we conclude that there seems to be a positive effect of SNAP participation on obesity rates for female participants and no such effect for males, a result that is consistent with several previous studies. However, an extensive sensitivity analysis reveals that the positive effect for females is sensitive to misclassification errors and to the conditional independence assumption. Thus analogous findings should also be used with caution unless examined under the prism of classification errors and of other assumptions used for the identification of causal parameters.     

What's Wrong with Risk Matrices?

Risk matrices—tables mapping "frequency" and "severity" ratings to corresponding risk priority levels—are popular in applications as diverse as terrorism risk analysis, highway construction project management, office building risk analysis, climate change risk management, and enterprise risk management (ERM). National and international standards (e.g., Military Standard 882C and AS/NZS 4360:1999) have stimulated adoption of risk matrices by many organizations and risk consultants. However, little research rigorously validates their performance in actually improving risk management decisions. This article examines some mathematical properties of risk matrices and shows that they have the following limitations. (a) Poor Resolution . Typical risk matrices can correctly and unambiguously compare only a small fraction (e.g., less than 10%) of randomly selected pairs of hazards. They can assign identical ratings to quantitatively very different risks ("range compression"). (b) Errors . Risk matrices can mistakenly assign higher qualitative ratings to quantitatively smaller risks. For risks with negatively correlated frequencies and severities, they can be "worse than useless," leading to worse-than-random decisions. (c) Suboptimal Resource Allocation . Effective allocation of resources to risk-reducing countermeasures cannot be based on the categories provided by risk matrices. (d) Ambiguous Inputs and Outputs . Categorizations of severity cannot be made objectively for uncertain consequences. Inputs to risk matrices (e.g., frequency and severity categorizations) and resulting outputs (i.e., risk ratings) require subjective interpretation, and different users may obtain opposite ratings of the same quantitative risks. These limitations suggest that risk matrices should be used with caution, and only with careful explanations of embedded judgments.     

Motivating knowledge sharing through a knowledge management system

Based on both economic and sociological theory, the effects of supervisory control and organizational support on the frequency and effort of individuals in contributing their personally held valuable knowledge to a “best practices-lessons learned, repository-based” knowledge management system (KMS) were compared. Supervisory control, as expected, had significant impact on frequency, but it also had unexpectedly significant influence on effort. When system variables—usefulness and ease of use—were controlled for, the organizational support measure had little effect on either outcome. These results provide greater support for economic-agency-theory motivators of knowledge sharing and lesser support for organizational support motivators than has been previously believed. They also emphasize the important impact of systems variables in motivating KMS use. Since the study was conducted in a government (joint civilian–military) organization, the organizational type may significantly influence the results. However, since the result is contrary to the conventional wisdom that suggests that a “knowledge-sharing culture” is all-important, at the very least, this study shows that the nature of the organization may moderate the relationship between the motivational approach and the outcomes.