挣脱生态牢笼的路径探幽——《共产党宣言》中马克思生态思想解读

《共产党宣言》蕴含着深刻的生态思想,其体系以人、社会、自然整体为背景,其核心观点认为生态问题是由资本主义生产方式引起的.马克思在唯物史观视野下,科学论证了资产阶级的所有制必然灭亡、共产主义必然实现的历史发展逻辑,廓清了人与人、人与自然之间双重和解的演化路径.其中关于科技提升、市场拓展、交通和通信发展等引起世界市场“生态扩张”的思想,对全球化程度日益加深境况下“生态文明”和“人类命运共同体”的构建具有重大的理论和实践指导价值.     

Applying a Treatment Effects Model to Investigate Public Amenity Effect on Physical Activity of the Elderly

The increasing elderly population puts significant health, economic, and social burdens on society. Physical activity is one of the most cost-effective ways to maintain the health of the elderly. This study adopts a treatment effects model to investigate the causal relationship between environment attributes and physical activity among the elderly, while taking endogeneity into account. The data were collected from 274 participants by face-to-face interviews in Taichung, Taiwan. Performing physical activity regularly in parks is the most important measure of the amount of physical activity by the elderly. Providing sufficient and accessible parks in metropolitan residential neighborhoods could be one of the most cost-effective ways to promote physical activity for the elderly living in midsize Asian cities.     

Social cohesion in Rwanda: Results from a public good experiment

We describe a public good experiment, a type of economic experiment commonly used to examine feelings of prosociality—that is, behaviour which is positive, helpful and intended to promote social acceptance and friendship—and community cohesion, carried out in Rwanda. Contributions in different parts of the country are affected by the local intensity of the 1994 genocide, with more generous contributions being made in areas where violence was greater. This supports earlier research indicating that conflict experience leads to greater prosociality. However, we also find that people who have not, themselves, been targets of violence give lower contributions than people who have. The considerable group‐related and regional differences in social behaviour may have implications for the country's policies to deal with social cohesion.     

Closure property of consistently varying random variables based on precise large deviation principles

Let X = {X₁, X₂, …} be a sequence of independent but not necessarily identically distributed random variables, and let η be a counting random variable independent of X. Consider randomly stopped sum S_η = ∑^η_{k = 1}X_k and random maximum S_(η) ? max?{S₀, …, S_η}. Assuming that each X_k belongs to the class of consistently varying distributions, on the basis of the well-known precise large deviation principles, we prove that the distributions of S_η and S_(η) belong to the same class under some mild conditions. Our approach is new and the obtained results are further studies of Kizinevi?, Sprindys, and ?iaulys (2016) and Andrulyt?, Manstavi?ius, and ?iaulys (2017).     

Oracle GMM estimation for misspecified models via thresholding

We propose a thresholding generalized method of moments (GMM) estimator for misspecified time series moment condition models. This estimator has the following oracle property: its asymptotic behavior is the same as of any efficient GMM estimator obtained under the a priori information that the true model were known. We propose data adaptive selection methods for thresholding parameter using multiple testing procedures. We determine the limiting null distributions of classical parameter tests and show the consistency of the corresponding block-bootstrap tests used in conjunction with thresholding GMM inference. We present the results of a simulation study for a misspecified instrumental variable regression model and for a vector autoregressive model with measurement error. We illustrate an application of the proposed methodology to data analysis of a real-world dataset.     

Children's experiences with an intervention aimed to prevent further physical abuse

Although many children across cultures are victims of physical abuse, few treatment models target these children and their parents. In Sweden, Combined Parent–Child Cognitive Behavioural Therapy for families at risk for child physical abuse has been successfully used according to pretreatment and posttreatment studies. However, few studies have explored how physically abused children experience treatment. This study includes 20 physically abused children aged 9–17 who completed Combined Parent–Child Cognitive Behavioural Therapy. Children had a positive overall impression of the treatment and highlighted addressing the abuse, as well as processing their experiences as particularly essential. Children described a positive transformation in their family life as a result of treatment, including violence cessation and bonding among family members. Children experienced the intervention as inclusive and child‐friendly. The implications of the promising findings are discussed.     

Bayesian density regression for discrete outcomes

We develop Bayesian models for density regression with emphasis on discrete outcomes. The problem of density regression is approached by considering methods for multivariate density estimation of mixed scale variables, and obtaining conditional densities from the multivariate ones. The approach to multivariate mixed scale outcome density estimation that we describe represents discrete variables, either responses or covariates, as discretised versions of continuous latent variables. We present and compare several models for obtaining these thresholds in the challenging context of count data analysis where the response may be over‐ and/or under‐dispersed in some of the regions of the covariate space. We utilise a nonparametric mixture of multivariate Gaussians to model the directly observed and the latent continuous variables. The paper presents a Markov chain Monte Carlo algorithm for posterior sampling, sufficient conditions for weak consistency, and illustrations on density, mean and quantile regression utilising simulated and real datasets.     

Hard thresholding regression

In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?₀‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology.     

The evolution of intellectual property strategy in innovation ecosystems: Uncovering complementary and substitute appropriability regimes

In this article, we attempt to extend and nuance the debate on intellectual property (IP) strategy, appropriation, and open innovation in dynamic and systemic innovation contexts. We present the case of four generations of mobile telecommunications systems (covering the period 1980–2015), and describe and analyze the co-evolution of strategic IP management and innovation ecosystems. Throughout this development, technologies and technological relationships were governed with different and shifting degrees of formality. Simultaneously, firms differentiated technology accessibility across actors and technologies to benefit from openness and appropriation of innovation. Our analysis shows that the discussion of competitiveness and appropriability needs to be expanded from the focal appropriability regime and complementary assets to the larger context of the innovation ecosystem and its cooperative and competitive actor relations, with dispersed complementary and substitute assets and technologies. Consequently, the shaping of complementary and substitute appropriability regimes is central when strategizing in dynamic and systemic innovation contexts. This holds important implications for the management of open innovation, innovation ecosystems, platforms, and coopetition.