“入世”的基本战略和主要对策

扩大开放,稳步迈向国际化 从外向化到国际化,提出已有多年。两者之间的区别,不仅在数量上,我国尤其是沿海省市的开放依赖度早就不低了;而在本质上,只要还实行高关税政策和少领域引资,总不是真正的国际化。逐步撤除关税壁垒,放开投资领域,正是“入世”,才使我国经济开始与国际市场相融合。不言而喻,这是机遇,又是冲击,要有恰当措施,获得正面效应。 “入世”意味着进一步开放,最直接的效应是扩大进出口贸易。开放以来,我国对外贸易的增长率一直高于经济增长率;就是在发生世界性金融危机后,国际贸易增长率顿然受挫,我国在稍…     

谁知圣人意,不尽书籍中——苏轼诗歌用典研究

苏轼用典比前人以及同时代的其他作家更为灵活多态,能够从典故来源处汲取创作灵感,转换体物视角,借鉴创作经验,进而推陈出新.尤其是在语典使用中,转益多师,取长补短,形成多样化的创作风格.同时,还不断改进和拓展用典方法,既影响到诗歌的修辞,又影响到命意谋篇,为诗歌带来多义性、情节化等特点,体现出“有为而作”、“辞达而已”、“无中生有以追求神似”的诗学主张.     

当前中国高校的哲学社会科学创新:观念与路径——基于全国50所高校的调查

2009年11月至2010年2月,围绕哲学社会科学创新问题,课题组在我国22个省(直辖市、自治区)的50所高校开展问卷调查。调查表明,在创新中实现繁荣发展,已成为当前中国高校哲学社会科学发展中的普遍期盼与核心主题。受访者对哲学社会科学创新能力构成的理解中,问题意识和前沿意识强烈,将学术发展与社会进步有机结合的思维取向突出;对相关主体推进哲学社会科学创新的意愿高度肯认,对其创新能力与成效的评价相对不高;对优化学术发展环境充满强烈期待,对研究者学术素质因素关注相对不足;肯定和认可推进创新的有关举措与建议,"改进评价机制"等被视为助益创新最需着力之处。深入推进高校哲学社会科学创新,应当坚持队伍建设为先,强化学风建设,增进方法自觉,着力培育战略科学家;坚持学术环境建设为重,优化政策和舆论环境,营造自由宽松的学术环境和聚焦质量与创新的评价环境;在遵循学术发展规律的基础上深化科研管理创新。     

近世金龙四大王考——官民互动中的民间信仰现象

金龙四大王是明清时期在运河区域具有较广泛影响力的漕运信仰.以往的研究在有关金龙四大王的最早记载、成神原因及最初形成区域等方面都有值得商榷的地方,并且未就这一信仰形成的过程进行解读.本文认为,金龙四大王最初是在江南地区形成的,明代永乐迁都北京以后,江南地区漕运负担加剧,从而在信仰层面形成了以护佑水运、漕运为主的神灵崇拜,并沿运河传播开来.金龙四大王信仰的形成过程典型地体现了官民互动的结果,官民双方力量的对比或态度的趋向会影响到对民间信仰的价值评判--是淫祀还是正祀.在官民互动的过程中,金龙四大王因在信仰的取向上更加契合国家正统理念,因而官方致祭的色彩越来越浓,最终被列入国家祀典,淡化了原有的民间性、地域性立场.     

合作共治:我国城市社区建设的路径——苏州市平江区社区体制创新探析

随着地方政府体制创新与职能转变.公民社会的发育与成熟必然提到议事日程.城市社区的发展是公民社会成熟的一个重要标志,社区的健康发展,一定意义上将推动与促进地方政府体制改革.目前,国内城市社区模式众多,有的从民主角度,有的侧重社区自治,有的强调地方政府服务.其中,苏州市平江区以体制创新为特色的社区建设引起了学术界的关注.苏州平江社区"1 4"体制架构的设想与法理依据,其体制创新的内涵与价值.对于探讨我国城市社区建设路径、配合地方政府职能转变形式、尝试地方政府与社区合作共治的治理之道以及充分吸纳社会力量推进公民社会成熟,都具有一定的参考价值与借鉴意义.     

Non parametric analysis of gap times for bivariate recurrent event data with cure fraction

Recurrent event data often arise in longitudinal studies. In many applications, subjects may experience two different types of events alternatively over time or a pair of subjects may experience recurrent events of the same type. Medical advances have made it possible for some patients to be cured such that the disease of interest does not recur. In this article, we consider non parametric analysis of bivariate recurrent event data with cure fraction. Using the inverse-probability weighted (IPW) approach, we propose non parametric estimators for the proportion of cured patients and for the joint distribution functions of bivariate recurrence times of the uncured ones. The asymptotic properties of the proposed estimators are established. Simulation study indicates that the proposed estimators perform well in finite samples.     

Conditional maximum likelihood estimation in semiparametric transformation model with LTRC data

Left-truncated data often arise in epidemiology and individual follow-up studies due to a biased sampling plan since subjects with shorter survival times tend to be excluded from the sample. Moreover, the survival time of recruited subjects are often subject to right censoring. In this article, a general class of semiparametric transformation models that include proportional hazards model and proportional odds model as special cases is studied for the analysis of left-truncated and right-censored data. We propose a conditional likelihood approach and develop the conditional maximum likelihood estimators (cMLE) for the regression parameters and cumulative hazard function of these models. The derived score equations for regression parameter and infinite-dimensional function suggest an iterative algorithm for cMLE. The cMLE is shown to be consistent and asymptotically normal. The limiting variances for the estimators can be consistently estimated using the inverse of negative Hessian matrix. Intensive simulation studies are conducted to investigate the performance of the cMLE. An application to the Channing House data is given to illustrate the methodology.     

Bernstein type inequalities for self-normalized martingales with applications

For self-normalized martingales with conditionally symmetric differences, de la Peña [A general class of exponential inequalities for martingales and ratios. Ann Probab. 1999;27(1):537–564] established the Gaussian type exponential inequalities. Bercu and Touati [Exponential inequalities for self-normalized martingales with applications. Ann Appl Probab. 2008;18:1848–1869] extended de la Peña's inequalities to martingales with differences heavy on left. In this paper, we establish Bernstein type exponential inequalities for self-normalized martingales with differences bounded from below. Moreover, applications to t-statistics and autoregressive processes are discussed.     

Analyzing Length-biased Data with Semiparametric Transformation and Accelerated Failure Time Models

Right-censored time-to-event data are often observed from a cohort of prevalent cases that are subject to length-biased sampling. Informative right censoring of data from the prevalent cohort within the population often makes it difficult to model risk factors on the unbiased failure times for the general population, because the observed failure times are length biased. In this paper, we consider two classes of flexible semiparametric models: the transformation models and the accelerated failure time models, to assess covariate effects on the population failure times by modeling the length-biased times. We develop unbiased estimating equation approaches to obtain the consistent estimators of the regression coefficients. Large sample properties for the estimators are derived. The methods are confirmed through simulations and illustrated by application to data from a study of a prevalent cohort of dementia patients.     

Triple-goal estimates in two-stage hierarchical models

The beauty of the Bayesian approach is its ability to structure complicated models, inferential goals and analyses. To take full advantage of it, methods should be linked to an inferential goal via a loss function. For example, in the two-stage, compound sampling model the posterior means are optimal under squared error loss. However, they can perform poorly in estimating the histogram of the parameters or in ranking them. 'Triple-goal' estimates are motivated by the desire to have a set of estimates that produce good ranks, a good parameter histogram and good co-ordinate-specific estimates. No set of estimates can simultaneously optimize these three goals and we seek a set that strikes an effective trade-off. We evaluate and compare three candidate approaches: the posterior means, the constrained Bayes estimates of Louis and Ghosh, and a new approach that optimizes estimation of the histogram and the ranks. Mathematical and simulation-based analyses support the superiority of the new approach and document its excellent performance for the three inferential goals.