Risk–risk governance in a low-carbon future: Exploring institutional,technological, and behavioral tradeoffs in climate geoengineering pathways

Deliberations are underway to utilize increasingly radical technological options to help address climate change and stabilize the climatic system. Collectively, these options are often referred to as “climate geoengineering.” Deployment of such options, however, can create wicked tradeoffs in governance and require adaptive forms of risk management. In this study, we utilize a large and novel set of qualitative expert interview data to more deeply and systematically explore the types of risk–risk tradeoffs that may emerge from the use of 20 different climate geoengineering options, 10 that focus on carbon dioxide or greenhouse gas removal, and 10 that focus on solar radiation management and reflecting sunlight. We specifically consider: What risks does the deployment of these options entail? What types of tradeoffs may emerge through their deployment? We apply a framework that clusters risk–risk tradeoffs into institutional and governance, technological and environmental, and behavioral and temporal dimensions. In doing so, we offer a more complete inventory of risk–risk tradeoffs than those currently available within the respective risk-assessment, energy-systems, and climate-change literatures, and we also point the way toward future research gaps concerning policy, deployment, and risk management.     

高绩效工作系统对员工敬业度的影响机理研究

基于对782名服务业和制造业员工进行的调查,分析了高绩效工作系统对员工敬业度的影响及作用机制。研究表明,高绩效工作系统对员工敬业度的积极影响不是直接的,工作幸福感的核心概念——积极情绪和工作满意度在其中起完全中介作用,而消极情绪的中介作用未得到支持。研究发现,高绩效工作系统实质上是动机激励的工作环境塑造系统,由此形成了激发员工内在工作动机和积极心理体验的组织环境。此外,进一步揭示了工作幸福感是促进员工敬业的关键环节,启示组织应加强员工工作中的情感管理,塑造员工积极的心理力量,从而构建幸福组织。     

C2C 环境中顾客重复购买行为的实证与建模

通过分析C2C 商家的交易记录, 发现单个商家的顾客重复购买次数呈幂律分布, 这与重复购买理论以往得到的购买次数为负二项分布的结论不同. 基于C2C 交易的实际情况, 建立了具有购买强化效应的购买概率模型, 模型很好的解释了顾客重复购买率呈幂律分布的现象.实证和模型表明, C2C 环境中, 顾客购买次数的分布具有很长的尾部, 大量顾客有低的购买次数, 而少数顾客有很高的重复购买次数;模型还揭示了巨大的潜在顾客数量和顾客多次购买的强化效应是造成重复购买分布呈幂律形式的重要原因.     

语用迁移的模因论阐释

从模因论的角度,分析语用迁移的成因。探讨二语习得者在学习目的语的过程中,二语模因库中的语言模因是如何合作或竞争,从而促进或阻碍学习者习得目的语。     

Smooth tail-index estimation

The two parametric distribution functions appearing in the extreme-value theory – the generalized extreme-value distribution and the generalized Pareto distribution – have log-concave densities if the extreme-value index γ∈[?1, 0]. Replacing the order statistics in tail-index estimators by their corresponding quantiles from the distribution function that is based on the estimated log-concave density ? f _n leads to novel smooth quantile and tail-index estimators. These new estimators aim at estimating the tail index especially in small samples. Acting as a smoother of the empirical distribution function, the log-concave distribution function estimator reduces estimation variability to a much greater extent than it introduces bias. As a consequence, Monte Carlo simulations demonstrate that the smoothed version of the estimators are well superior to their non-smoothed counterparts, in terms of mean-squared error.     

A two-parameter estimator in the negative binomial regression model

In this article, a two-parameter estimator is proposed to combat multicollinearity in the negative binomial regression model. The proposed two-parameter estimator is a general estimator which includes the maximum likelihood (ML) estimator, the ridge estimator (RE) and the Liu estimator as special cases. Some properties on the asymptotic mean-squared error (MSE) are derived and necessary and sufficient conditions for the superiority of the two-parameter estimator over the ML estimator and sufficient conditions for the superiority of the two-parameter estimator over the RE and the Liu estimator in the asymptotic mean-squared error (MSE) matrix sense are obtained. Furthermore, several methods and three rules for choosing appropriate shrinkage parameters are proposed. Finally, a Monte Carlo simulation study is given to illustrate some of the theoretical results.     

The negative binomial–beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial–beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.     

教育服务产出核算分析

教育服务是服务核算中的一个重要部分。本文讨论教育服务的定义和服务产出的数量单位。研究教育服务的核算范围和计算教育服务产出价值的方法,以及教育服务的质量调整问题。最后,举例使用产出指标方法计算教育产出。     

教师课堂教学质量综合评价方法研究

教师课堂教学质量综合评价以课堂教学质量评价指标体系为基础,综合评价方法主要包括指标加权平均法和模糊综合评价法。难点是评价指标的设计和量化处理,权集的构造。对评价结果的分析可采用绝对评价(等级判断),相对评价,动态评价(个体差异的评价)。     

ESTIMATING A RATIO OF MEANS FROM BIVARIATE COUNTS WITH APPLICATIONS IN STEREOLOGY

In survey sampling and in stereology, it is often desirable to estimate the ratio of means θ= E(Y)/E(X) from bivariate count data (X, Y) with unknown joint distribution. We review methods that are available for this problem, with particular reference to stereological applications. We also develop new methods based on explicit statistical models for the data, and associated model diagnostics. The methods are tested on a stereological dataset. For point‐count data, binomial regression and bivariate binomial models are generally adequate. Intercept‐count data are often overdispersed relative to Poisson regression models, but adequately fitted by negative binomial regression.