地方院校人才培养中若干问题的调查研究

高等教育的国际化和大众化,既给地方高校带来了机遇,也带来了挑战,其中最突出的就是人才培养问题。如何培养和造就具有创新精神和创新能力的高素质人才,是地方院校亟待解决的重要课题。以我校调查问卷结果为切入点,力求理清目前地方院校人才培养的困境,进而提出合理的对策与建议。     

从贵阳市看地方政府对城市品牌形象传播的管理和引导

城市的形象是传播资源和传播渠道综合作用的结果,而无论哪种城市形象的传播,政府都是城市形象定位的领导者。像贵阳市那样,准确的城市形象定位能反映一个城市的特色和优势,激发城市的内在潜力,为城市特定时期的发展提供目标指向。     

Estimation on Varying-Coefficient Partially Linear Model With Different Smoothing Variables

The authors give the estimation on the varying-coefficient partially linear regression model with different smoothing variables. The efficient estimators of the intercept function and the coefficient functions are obtained by a one-step back-fitting technique based on their initial estimators given by local linear technique and the averaged method. Furthermore, their asymptotic normalities are given. Some simulation studies are used to illustrate the performances of the estimation.     

Bandwidth selection for local linear regression smoothers

Summary. The paper presents a general strategy for selecting the bandwidth of nonparametric regression estimators and specializes it to local linear regression smoothers. The procedure requires the sample to be divided into a training sample and a testing sample. Using the training sample we first compute a family of regression smoothers indexed by their bandwidths. Next we select the bandwidth by minimizing the empirical quadratic prediction error on the testing sample. The resulting bandwidth satisfies a finite sample oracle inequality which holds for all bounded regression functions. This permits asymptotically optimal estimation for nearly any regression function. The practical performance of the method is illustrated by a simulation study which shows good finite sample behaviour of our method compared with other bandwidth selection procedures.     

On influence diagnostic in univariate elliptical linear regression models

We discuss in this paper the assessment of local influence in univariate elliptical linear regression models. This class includes all symmetric continuous distributions, such as normal, Student-t, Pearson VII, exponential power and logistic, among others. We derive the appropriate matrices for assessing the local influence on the parameter estimates and on predictions by considering as influence measures the likelihood displacement and a distance based on the Pearson residual. Two examples with real data are given for illustration.     

On edge orienting methods for graph coloring

We consider the problem of orienting the edges of a graph so that the length of a longest path in the resulting digraph is minimum. As shown by Gallai, Roy and Vitaver, this edge orienting problem is equivalent to finding the chromatic number of a graph. We study various properties of edge orienting methods in the context of local search for graph coloring. We then exploit these properties to derive four tabu search algorithms, each based on a different neighborhood. We compare these algorithms numerically to determine which are the most promising and to give potential research directions.     

Counter-geographies: The campaign against rationalisation of agricultural research stations in New South Wales, Australia

This paper discusses an example of community action mounted in a rural region of New South Wales, Australia, in response to proposals by the State Government to rationalise agricultural research stations operated by the Department of Primary Industries. Informed by a Foucaultian understanding of power and the concept of governmentality, neoliberalism is theorised as being the broad governmental context in which rationalisation proposals were put forward. Recent literature drawing on this theoretical perspective has emphasised that neoliberalism is enacted through a relationship of power, and is not monolithic or inevitable. Neoliberalism is always negotiated by those seeking to govern and those who are the object of such governmental actions. This paper analyses how plans to rationalise publicly funded agricultural research stations were opposed by those seeking to keep research facilities open in the case study area. The paper discusses the methods and scope of community action and, drawing on interviews, identifies a series of discourses articulated by campaigners. Non-local actors were depicted as uncaring and insensitive. In contrast, campaigners discussed the emergence of a ‘city-country divide’ in domestic politics; the need for specialist agricultural knowledge given the region's unique geographical location; and local impacts of an economic, social and emotional nature. Central were discourses of maintaining community, tradition, and continuity in unique local places defined by their climate, biophysical environment and economy. These were ‘counter-geographies’ that sought (successfully, it would transpire) to disrupt the state's imagined geography of a homogenous and flexible administrative space in which research services could be relocated wherever most efficient. Important too were embodied resistances to the way rural industries and people were subjected. Campaigners refused to accept preferred codes of neoliberal behaviour (particularly mobility and rationality) and instead demanded respect for their careers, families and communities. Important considerations are suggested for further research on impacts and negotiations of neoliberalism. This study particularly highlights the successes—as well as contradictions and limitations—of arguments that construct rural places as socialised, unique and unfairly treated (by governments), in opposition to metropolitan dominance and ‘placeless’ neoliberalism.     

Biased Bootstrap Methods for Reducing the Effects of Contamination

Contamination of a sampled distribution, for example by a heavy-tailed distribution, can degrade the performance of a statistical estimator. We suggest a general approach to alleviating this problem, using a version of the weighted bootstrap. The idea is to 'tilt' away from the contaminated distribution by a given (but arbitrary) amount, in a direction that minimizes a measure of the new distribution's dispersion. This theoretical proposal has a simple empirical version, which results in each data value being assigned a weight according to an assessment of its influence on dispersion. Importantly, distance can be measured directly in terms of the likely level of contamination, without reference to an empirical measure of scale. This makes the procedure particularly attractive for use in multivariate problems. It has several forms, depending on the definitions taken for dispersion and for distance between distributions. Examples of dispersion measures include variance and generalizations based on high order moments. Practicable measures of the distance between distributions may be based on power divergence, which includes Hellinger and Kullback–Leibler distances. The resulting location estimator has a smooth, redescending influence curve and appears to avoid computational difficulties that are typically associated with redescending estimators. Its breakdown point can be located at any desired value ε∈ (0, ½) simply by 'trimming' to a known distance (depending only on ε and the choice of distance measure) from the empirical distribution. The estimator has an affine equivariant multivariate form. Further, the general method is applicable to a range of statistical problems, including regression.     

区域和谐与地方政府区际行政行为创新研究

区际行政行为研究,针对的是地方政府行为中与其他地区有互动关系,对其他地区具有影响作用的一部分行为,地方政府区际行政行为的合作与否,直接关系区域之间的和谐共荣。当前,扭曲的区际行政行为设立起无形的行政壁垒,已经成为制约区域经济一体化的瓶颈,弹奏着区域发展的不和谐音符。分析地方政府博弈心理,认为地方政府区际行政行为创新是促进区域和谐发展的有效"解决之道"。     

Robust models in probability sampling

In the estimation of a population mean or total from a random sample, certain methods based on linear models are known to be automatically design consistent, regardless of how well the underlying model describes the population. A sufficient condition is identified for this type of robustness to model failure; the condition, which we call 'internal bias calibration', relates to the combination of a model and the method used to fit it. Included among the internally bias-calibrated models, in addition to the aforementioned linear models, are certain canonical link generalized linear models and nonparametric regressions constructed from them by a particular style of local likelihood fitting. Other models can often be made robust by using a suboptimal fitting method. Thus the class of model-based, but design consistent, analyses is enlarged to include more realistic models for certain types of survey variable such as binary indicators and counts. Particular applications discussed are the estimation of the size of a population subdomain, as arises in tax auditing for example, and the estimation of a bootstrap tail probability.