青少年暴力行为的预测和评估

青少年暴力行为是全球广泛关注的公共卫生和社会问题,了解青少年暴力行为的风险因素和预测方法有助于减少青少年暴力行为的发生.本文对青少年暴力的个体因素、社会心理因素、生物学因素进行了总结,对预测和评估研究的现状进行了复习,以期对青少年暴力行为发生的减少和进一步深入研究有所帮助.     

未来二十年流动人口犯罪对辽宁社会稳定的影响及对策研究

当前,流动人口犯罪已成为 社会密切关注,公安机关亟需解决的 焦点问题之一。振兴辽宁老工业基地 的前提是政治稳定和社会安定,因此, 加强流动人口管理,积极预防和控制 流动人口犯罪,显得越发重要和迫在 眉睫。本文分析了辽宁流动人口犯罪 的现状,特点以及成因,对未来二十年 辽宁流动人口犯罪发展趋势进行了预 测,并在此基础上,提出了有效预防和 控制流动人口犯罪的方法和策略。     

Do local elections predict the outcome of the next general election? Forecasting British general elections from local election national vote share estimates

This article outlines a method for forecasting British general elections from national level vote shares at local elections. Although local elections are notionally ‘local’, the evidence suggests that they at least partly mirror national electoral fortunes. A simple general election vote share on local election vote share regression model that accounts for partisan differences and incumbency effects fits past data with reasonable accuracy. Based on the results of the 2013 and 2014 local elections, the model forecast a 56% probability of hung parliament, with a 78% probability of the Conservatives receiving the largest share of the vote.     

探讨快速反应的产品需求链管理的方法

文中就市场需求的变化引出加强产品需求链的管理,提出了建立一条快速反应的产品需求供应链的多种方法,具有很强的现实意义。     

Did you see it coming? Explaining the accuracy of voter expectations for district and (sub)national election outcomes in multi-party systems

The expectations of voters regarding election outcomes appear to be mostly influenced by their own political preferences. This raises two important questions. First, once partisan predispositions have been accounted for, how much do other variables like interest in the campaign, election news attentiveness, political knowledge, education or competitiveness help to explain one’s ability at predicting election outcomes? Second, does one’s level of sophistication moderate the link between political preferences and forecasting abilities? To answer these questions, I mobilize data from seven elections taken at the district and (sub)national levels. I also introduce a new measure of forecasting ability—the cumulative Brier score index. In most cases, variables other than preferences and knowledge have little or no influence on the accuracy of voters’ expectations both at the (sub)national and district levels. Political knowledge is positively associated with citizens’ forecasting abilities; however, it does not appear to moderate the preference–expectation link. This result contradicts findings from existing work and holds important implications for the study of citizen forecasting.     

Piecing it all together and forecasting who governs: The 2015 British general election

This paper discusses a new probabilistic forecasting method that was designed for the 2015 British general election. It proceeds in a series of steps from opinion poll averaging, forecasting national-level vote shares and uncertainty estimates, and subsequent simulation of hypothetical election results, through modelling of constituency polls and survey data to identify and adjust for patterns in the constituency-level variation in party performance, and finally to probabilistic forecasting of seat outcomes and of different combinations of parties commanding relevant governing majorities in parliament.     

Forecasting proportional representation elections from non-representative expectation surveys

This study tests non-representative expectation surveys as a method for forecasting elections. For dichotomous forecasts of the 2013 German election (e.g., who will be chancellor, which parties will enter parliament), two non-representative citizen samples performed equally well than a benchmark group of experts. For vote-share forecasts, the sample of more knowledgeable and interested citizens performed similar to experts and quantitative models, and outperformed the less informed citizens. Furthermore, both citizen samples outperformed prediction markets but provided less accurate forecasts than representative polls. The results suggest that non-representative surveys can provide a useful low-cost forecasting method, in particular for small-scale elections, where it may not be feasible or cost-effective to use established methods such as representative polls or prediction markets.     

Forecasting the 2016 General Election in Jamaica

The objective of the article is to explain the methodologies and the findings of the 2016 Jamaican General Election forecasts. The Good Judgment Project’s CHAMPSKNOW system was applied using qualitative and quantitative methods. The research question was: what were the probabilities of the Jamaica Labour Party (JLP) or the People’s National Party (PNP) winning the 25 February 2016 General Election? The data were drawn from election results and macro-economic variables from 1962 to 2015; polls from 1976 to 2016; campaign ads; election newspaper stories; constituency fund disbursements and independent surveys in marginal seats. The results showed that the JLP had a greater number of ads with better and clearer policy contents than the PNP ads. The JLP also received more positive news coverage during the campaign. MPs who spent a large part of their constituency funds on welfare were more likely to win. The PNP had more garrison, traditional and marginal seats than the JLP so the PNP had the edge. Moreover, the data from the independent surveys and the macro-economic analyses indicated the likelihood of a PNP win. The national polls revealed a statistical dead heat but the forecasts started with the governing PNP having a slightly greater probability of winning because of its active political business cycle in which the PNP was rolling out programmes throughout the country in the election year. The forecasts were revised when the JLP narrowed the gap because the PNP refused to participate in the national debate, which generated negative news about the PNP. The final forecast said the election would be close with the PNP having the edge. However, the JLP’s tax plan was a wild card, which gave the party the edge with a one-seat victory.     

How We Feel about the Deal

Recent experimental research suggests that humans are prone to systematic errors when determining how they currently feel, imagining how they will feel about future events, remembering how they have felt about past events, and understanding the preferences that underlie their decisions. In this article, we briefly review three basic assumptions that are called into question by recent findings regarding specific kinds of errors that people are prone to make. We suggest that this line of research has important implications for negotiation theory, research, advice, and practice.     

Using ARIMA models to predict prison populations

In this study a time-series model for predicting Louisiana's prison population was developed using the iterative Box-Jenkins modeling methodologyidentification, estimation, and diagnostic checking. The time-series forecasts were contrasted with results of regression models and an exponential smoothing model. The results indicate that the time-series model is the superior model as indicated by the usual measures of predictive accuracy. When compared with actual data the predictions appeared sufficiently adequate to meet the needs of the correctional system for short-term planning.