局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

高校哲学社会科学研究评价的本质要求及其制度建设

建设具有中国特色、中国风格、中国气派的哲学社会科学,一直是我国哲学社会科学繁荣发展的根本目的.提升高校哲学社会科学繁荣发展水平,离不开科学有效的哲学社会科学研究评价.坚持党的领导、"二为"方向和"双百"方针是哲学社会科学繁荣发展的根本保障,坚持"质量为本"和"创新至上"是哲学社会科学繁荣发展的必然要求,坚持科学权威和公开透明是哲学社会科学研究评价的现实需要.结合当前高校哲学社会科学研究评价中"量化评价下数量与质量的关系论辩","学术评价与科研管理评价的边界异化"和"学术权力和行政权力的制度规制"三大问题聚讼,文章建议通过强化学术成果质量保障机制、优化学术共同体工作机制、构建学术争鸣长效机制和完善学术成果转化应用机制等制度建设,推动构建科学权威、公开透明的哲学社会科学研究评价体系,以期进一步改善新时代高校哲学社会科学研究评价工作.     

中国“碳中和”目标的实现路径与模式选择

围绕中国碳中和目标的实现路径与模式选择问题，提出了一个中国应对气候变化整体治理模式，即多阶段混合主导型碳中和实现模式。这一模式是以国家为核心，在一定时期和内外环境约束下，通过减排和增汇路径，对中国境内由人类活动造成的CO2排放与人为CO2吸收量之间关系进行调整和平衡的过程；其内部由宏观、中观和微观三层结构组成，每层结构各不相同。多阶段混合主导型碳中和实现模式的提出，拓展和完善了气候变化整体治理理论，为气候变化治理提供了机制借鉴。     

Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method.     

When Working Hard Is Not Enough for Female and Racial/Ethnic Minority Apprentices in the Highway Trades

Drawing on employment records, qualitative interviews, and a survey, we explore the experiences of apprentices in the highway trades in Oregon. We demonstrate that female and racial/ethnic minority apprentices have lower rates of recruitment and retention and disproportionately face challenges with interpersonal interactions, hiring practices, and supervisory practices. Yet, we find a pervasive narrative that attributes apprentices' success to “hard work,” which contributes to the legitimacy of these inequalities. Consistent with the conceptualization of work organizations as inequality regimes, we argue that the apprenticeship system has policies, practices, and ideologies that are on the surface gender and race/ethnicity neutral, yet lead to the perpetuation of inequalities.     

小学教育专业之教育专业课程建构的逻辑

小学教育专业的培养目标决定了小学教育专业课程体系的基本逻辑：以通识课程奠基，以学科课程立命，以教育课程定向。教育专业课程是小学教育专业课程体系的重要构成部分。其基本逻辑结构包括学科课程、活动课程和技能课程。学科课程可按照认识小学教育、理解小学教育教学过程、学会研究小学教育的逻辑来建构；活动课程可按照感知小学教育、实践小学教育、研究小学教育来建构；技能课程可按照小学教师公共职业技能和学科职业技能来建构。     

A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covariates or regressors). Although multinomial logit is widely used in both the social and economic sciences, the interpretation of regression coefficients may be tricky, as the effect of covariates on the probability distribution of the response variable is nonconstant and difficult to quantify. The ternary plots illustrated in this article aim at facilitating the interpretation of regression coefficients and permit the effect of covariates (either singularly or jointly considered) on the probability distribution of the dependent variable to be quantified. Ternary plots can be drawn both for ordered and for unordered categorical dependent variables, when the number of possible outcomes equals three (trinomial response variable); these plots allow not only to represent the covariate effects over the whole parameter space of the dependent variable but also to compare the covariate effects of any given individual profile. The method is illustrated and discussed through analysis of a dataset concerning the transition of master’s graduates of the University of Trento (Italy) from university to employment.     

Fast and approximate exhaustive variable selection for generalised linear models with APES

We present APproximated Exhaustive Search (APES), which enables fast and approximated exhaustive variable selection in Generalised Linear Models (GLMs). While exhaustive variable selection remains as the gold standard in many model selection contexts, traditional exhaustive variable selection suffers from computational feasibility issues. More precisely, there is often a high cost associated with computing maximum likelihood estimates (MLE) for all subsets of GLMs. Efficient algorithms for exhaustive searches exist for linear models, most notably the leaps‐and‐bound algorithm and, more recently, the mixed integer optimisation (MIO) algorithm. The APES method learns from observational weights in a generalised linear regression super‐model and reformulates the GLM problem as a linear regression problem. In this way, APES can approximate a true exhaustive search in the original GLM space. Where exhaustive variable selection is not computationally feasible, we propose a best‐subset search, which also closely approximates a true exhaustive search. APES is made available in both as a standalone R package as well as part of the already existing mplot package.     

需求牵引课题培养材料领域研究生爱国担当之志

培养研究生爱国担当之志是研究生教育的根本，是科研育人的生动体现，是落实全国高校思想政治工作会议精神与全国研究生教育会议精神的核心。以材料领域研究生培养为例，探讨需求牵引课题激发与培养研究生爱国担当之志的路径与成效。结合自主创新研究成果与航天迫切需求，激发学生奉献与担当之志，立志为我国航天强国事业贡献青春与力量，担当时代赋予的重任。实现将科学研究与思想引领有机融合，引导学生建立主动将个人成长与国家发展和中华民族伟大复兴相结合的信念，培养学生既具有过硬材料创新本领，又具有自信、爱国、奉献、担当意识，为中国特色社会主义现代化建设培养德才兼备的材料领域创新拔尖领军人才。