The Pro‐Elderly Bias of Social Policies in Israel: A Historical‐Institutional Account

Accelerated population ageing and high voting turnout rates among elderly voters in recent decades have led many social scientists to predict increasing pro‐elderly biases in the social policies of mature welfare states. This article investigates and empirically estimates the evolving age orientation of social policies in Israel, which is a comparatively young society that has nevertheless aged significantly since independence in 1948. We present a historical and qualitative overview of the development of policy efforts towards different age groups and develop an Elderly/Non‐elderly Spending Ratio at four points in time between 1975 and 2005. We argue that in its first five decades, the Israeli welfare state uniquely combined a broadly universalistic and citizenship‐based outlook with a number of significant particularistic spending biases towards specific subgroups. But from the second half of the 1990s onwards, the pro‐elderly policy bias of the Israeli welfare state has strongly increased. These findings support Lynch's thesis for 21 OECD countries, which posits that a shift from a universal to a more occupationally based institutional model of welfare will result in a higher pro‐elderly bias of social spending.     

Pitman nearness comparisons of Stein-type estimators for regression coefficients in replicated experiments

This paper presents a comparative study of the performance properties of one unbiased and two Stein-type estimators for combining the estimates of coefficients in a linear regression model when data sets are available from replicated experiments conducted at possibly different stations.     

Seeing The World Through Rose‐colored Glasses? Neglect of Consensus Information in Young Children's Personality Judgments

The present study examined the use of consensus information in early childhood. Ninety‐six three‐ to six‐year‐olds watched a demonstration that depicted the positive or negative behavior of one or several actors toward a recipient (low vs. high consensus, respectively). Subsequently, participants made behavioral predictions and personality judgments about the actors and recipients. Participants viewed all story characters favorably and were reluctant to assign blame for negative outcomes, although the appropriate use of consensus information increased with age for behavioral predictions. These findings suggest that there is a positivity bias in young children's personality judgments even in the face of explicit contradictory behavioral evidence. Children's early ‘theory of personality’ is apparently driven by a baseline assumption that people are nice.     

Generalizing from PRSA to public relations: How to accommodate sampling bias in public relations scholarship

One of the major challenges to conducting externally valid, quantitative scholarship in public relations is accessing samples of practitioners that are willing to participate in academic research. One sampling frame would naturally be the membership of the Public Relations Society of America (PRSA), which is the world's largest professional association for public relations practitioners. Yet, even if the question of access were resolved, there still remains the question of external validity, i.e., the issue of whether and to what extent the membership of PRSA (or any other sampling frame) reflects the population of public relations practitioners in general.     

双重维度看陷阱抗辩之证明责任

刑事诉讼中被告人以陷阱侦查作为其出罪的抗辩理由之一,此抗辩即为陷阱抗辩。出于对控辩双方证明能力和证明手段对比之考量,陷阱抗辩的证明责任分为客观合法性证明和主观倾向性证明两个层面,分别由控辩双方承担。这种独特的证明责任构成是诱惑侦查案件中重要的分配正义的方式之一。     

Bias of S 2 in Linear Regressions with Dependent Errors

Bounds are given for the expected value of the estimator of the error variance in linear regressions, when the errors are dependent or heteroscedastic. The bounds are valid irrespective of the covariance structure between the errors. Necessary and sufficient conditions to attain the bounds are supplied.     

Sample-based Maximum Likelihood Estimation of the Autologistic Model

New recursive algorithms for fast computation of the normalizing constant for the autologistic model on the lattice make feasible a sample-based maximum likelihood estimation (MLE) of the autologistic parameters. We demonstrate by sampling from 12 simulated 420×420 binary lattices with square lattice plots of size 4×4, …, 7×7 and sample sizes between 20 and 600. Sample-based results are compared with ‘benchmark’ MCMC estimates derived from all binary observations on a lattice. Sample-based estimates are, on average, biased systematically by 3%–7%, a bias that can be reduced by more than half by a set of calibrating equations. MLE estimates of sampling variances are large and usually conservative. The variance of the parameter of spatial association is about 2–10 times higher than the variance of the parameter of abundance. Sample distributions of estimates were mostly non-normal. We conclude that sample-based MLE estimation of the autologistic parameters with an appropriate sample size and post-estimation calibration will furnish fully acceptable estimates. Equations for predicting the expected sampling variance are given.     

Comparison of designs for multivariate generalized linear models

The purpose of this paper is to discuss response surface designs for multivariate generalized linear models (GLMs). Such models are considered whenever several response variables can be measured for each setting of a group of control variables, and the response variables are adequately represented by GLMs. The mean-squared error of prediction (MSEP) matrix is used to assess the quality of prediction associated with a given design. The MSEP incorporates both the prediction variance and the prediction bias, which results from using maximum likelihood estimates of the parameters of the fitted linear predictor. For a given design, quantiles of a scalar-valued function of the MSEP are obtained within a certain region of interest. The quantiles depend on the unknown parameters of the linear predictor. The dispersion of these quantiles over the space of the unknown parameters is determined and then depicted by the so-called quantile dispersion graphs. An application of the proposed methodology is presented using the special case of the bivariate binary distribution.     

CSRC处罚的“选择性偏见”——基于业绩预测的证据

通过对业绩预测违规这一特殊违规事项的分析发现,违规而未受到处罚的样本在盈利水平和盈利能力方面显著地高于被处罚的样本,前者亏损的比例、业绩下滑的幅度以及比例显著地低于后者。违规和未违规样本的对比分析则显示,违规而未受到处罚的样本和未违规的样本在上述方面不存在显著差异。由此可见,CSRC对被处罚样本的选择带有一定程度的"选择性偏见"。     

Lay Understanding of Synergistic Risk: The Case of Radon and Cigarette Smoking

The combination of radon and smoking produces a synergistic risk of lung cancer. Lay understanding of this risk was examined from the perspectives of mental models theory, the psychometric approach to risk perception, and optimistic bias. As assessed by interview, participants ( N = 50) had more extensive mental models for the risks of smoking than for the risks of radon or the combination of radon and smoking; 32% knew little or nothing about radon. Despite reading an informational brochure, their risk-perception ratings of the three hazards showed no perception of the synergy between smoking and radon risk, although the combined hazard was rated as less familiar but more controllable than the average of the single hazards ( p < .01). No evidence of optimistic bias for the health consequences of radon, or the combination of radon and smoking was observed. Participants appeared to be combining the single-hazard risks subadditively to arrive at their combined-hazard risk perceptions. Further research on the integration of perceived risks would be beneficial for designing optimal communications about synergistic risk.