Limiting labels: Opportunities to learn and college readiness among English language learners

Over a fifth of California's public schools' students have limited access to college and career pathways due to being labeled an “English-language learner (ELLs).” As reported by the California Department of Education, in the 2017–2018 school year, of the over 6.2 million students in California, nearly 1.3 million students are categorized as ELLs. The ELL label states students “whose difficulties in speaking, reading, writing, or understanding English may (my emphasis) limit his or her ability to (1) achieve in classrooms where English is the language of instruction and (2) access opportunities to fully participate in society.” Aligned with deficit thinking models, the US school system interprets “may” as “will” and makes decisions that negatively impact a large body of students across the country. The growing body of research reveals that many with the ELL label have been and continue to be intentionally underserved, limited access to postsecondary education, tracked into low-rigor and stigmatizing course pathways, and are deliberately unsupported to become college-ready, furthering the inequities in education and limiting options for quality k-12 educational experiences. The system becomes blinded by the label and ignores students with ELL labels' abilities and capacities to learn. So how are students with ELL labels supposed to become college-ready, let alone career-ready? For the purposes of this critical literature review, I will focus on exploring the existing structures that define “college-readiness” and the disparities created by the intentional tracking of students with the ELL label in comparison to their non-ELL peers.     

政府会计规则执行机制问题研究——基于契约理论的视角

会计规则执行机制是在会计规则制定权安排给第三方机构之后,为了解决经济组织接受和公允地、不偏不倚地执行通用会计规则两个问题的备选方案的集合。有效的会计规则执行机制应能使经济组织的信息成本和代理成本总和达到经济点。会计规则执行机制包含强力机制和压力机制,前者依赖于立法和行政权威,后者依靠经济组织的资源依赖压力,两者各具优缺点。政府契约集合特征决定了政府会计规则的二元性,即收付实现制的预算会计制度和权责发生制的政府会计准则,前者适宜刚性的强制机制,后者适宜柔性的压力机制。在我国,政府预算契约具有同质性而债务契约存在异质性,且政府层级多、数量大、规模差异悬殊。为提升我国政府会计规则的执行效率和效果,应按照政府层级、契约结构特点等对政府预算会计和政府财务会计实行差异化的执行机制选择和构建。     

碳交易机制下零售商合作的费用分配研究

在一个由单供应商和多个零售商组成的二阶供应链中,研究碳交易机制下多零售商合作的订货决策问题。对完全信息下零售商合作的费用分配问题,应用合作博弈理论建立了费用分配的博弈模型,证明了博弈为子模博弈且设计了属于核心的费用分配方案,该方案不仅可通过总体单调分配机制实现而且可使大联盟长远稳定。对不完全信息下零售商合作的费用分配问题,证明了纯策略纳什均衡的存在性。研究结果表明,零售商的合作不仅能降低总费用,而且能降低碳排放量;各零售商在不完全信息下分担的费用大于完全信息下分担的费用。     

世界大变局下中国外交能力建设:目标与路径

外交能力是国家实力的重要构成要素,外交能力大小是影响一国国际地位和影响力的重要变量。中国特色大国外交的时代命题,就是要主动塑造中国作为一个世界大国所应有的外交体系和外交能力,外交能力建设自始便是中国特色大国外交的重要内容。新时代中国外交能力建设,以“两个大局”为时代坐标,着眼塑造和用好中国发展的重要战略机遇期,为实现中华民族伟大复兴提供更加有力的保障,为人类进步作出更大贡献。中国外交能力建设应以外交体制机制建设为基础,以外交理论创新为引领,以外交布局的谋划和推进为主线,以战略实施能力的全面提升为支撑。外交能力建设是一个系统工程,需要有效实现国家实力、战略目标、外交方式的相互匹配,同步推进外交体制机制改革与外交人才队伍建设,注重外交实务也要加强学术发展和智库建设。     

A Dominance-Based Rough Set Approach for an Enhanced Assessment of Seasonal Influenza Risk

Accounting for about 290,000–650,000 deaths across the globe, seasonal influenza is estimated by the World Health Organization to be a major cause of mortality. Hence, there is a need for a reliable and robust epidemiological surveillance decision-making system to understand and combat this epidemic disease. In a previous study, the authors proposed a decision support system to fight against seasonal influenza. This system is composed of three subsystems: (i) modeling and simulation, (ii) data warehousing, and (iii) analysis. The analysis subsystem relies on spatial online analytical processing (S-OLAP) technology. Although the S-OLAP technology is useful in analyzing multidimensional spatial data sets, it cannot take into account the inherent multicriteria nature of seasonal influenza risk assessment by itself. Therefore, the objective of this article is to extend the existing decision support system by adding advanced multicriteria analysis capabilities for enhanced seasonal influenza risk assessment and monitoring. Bearing in mind the characteristics of the decision problem considered in this article, a well-known multicriteria classification method, the dominance-based rough set approach (DRSA), was selected to boost the existing decision support system. Combining the S-OLAP technology and the multicriteria classification method DRSA in the same decision support system will largely improve and extend the scope of analysis capabilities. The extended decision support system has been validated by its application to assess seasonal influenza risk in the northwest region of Algeria.     

Inequality of opportunity and (unequal) opportunities in the youth labour market: How is the Arab world different?

The Middle East and North Africa (MENA) labour market is emblematic of widespread youth unemployment and high discouragement rates, experiencing disproportionately high levels of unemployment among educated young people. Using ILO School-to-Work Transition Surveys for Egypt, Jordan and Tunisia, the authors explore whether this is related to inequality of opportunity or to deeper structural characteristics that create a mismatch between skill demand and supply on the labour market. The low availability of high-skilled jobs and the low value placed on skills gained through the system of vocational training are found to have high explanatory power.     

A comparison of models using removal effort to estimate animal abundance

This paper compares methods for modeling the probability of removal when variable amounts of removal effort are present. A hierarchical modeling framework can produce estimates of animal abundance and detection from replicated removal counts taken at different locations in a region of interest. A common method of specifying variation in detection probabilities across locations or replicates is with a logistic model that incorporates relevant detection covariates. As an alternative to this logistic model, we propose using a catch–effort (CE) model to account for heterogeneity in detection when a measure of removal effort is available for each removal count. This method models the probability of detection as a nonlinear function of removal effort and a removal probability parameter that can vary spatially. Simulation results demonstrate that the CE model can effectively estimate abundance and removal probabilities when average removal rates are large but both the CE and logistic models tend to produce biased estimates as average removal rates decrease. We also found that the CE model fits better than logistic models when estimating wild turkey abundance using harvest and hunter counts collected by the Minnesota Department of Natural Resources during the spring turkey hunting season.     

On optimal1iy criteria in simultaneous interval estimation

We investigate the optimality of the estimator θ(Qα ) when L(θ ) is the set of all normalized linear functions of θ and all elements in L(θ ) are of “equal importance.”     

A confidence set for that <Emphasis Type=Italic>x</Emphasis>-coordinate where a quadratic regression model has a given gradient

An exact confidence set for that x-coordinate where a quadratic regression model has a given gradient is derived. The limits of the confidence set are given by mathematical formulae. They are implemented in Fortran programs that can be downloaded from the web. The confidence set need not be an interval. Its increase and its changing shape for increasing confidence level is extensively described and visualized in a figure that relates to data from nitrogen-rate trials in Germany. The wheat yields in this example are modeled as quadratic functions of the nitrogen input in order to determine a confidence set for the economically optimum nitrogen fertilization. The disadvantage that the confidence set does not distinguish between concave and convex parabolae, between profit maxima and minima, is also discussed.     

Higher order asymptotic computation of Bayesian significance tests for precise null hypotheses in the presence of nuisance parameters

The full Bayesian significance test (FBST) was introduced by Pereira and Stern for measuring the evidence of a precise null hypothesis. The FBST requires both numerical optimization and multidimensional integration, whose computational cost may be heavy when testing a precise null hypothesis on a scalar parameter of interest in the presence of a large number of nuisance parameters. In this paper we propose a higher order approximation of the measure of evidence for the FBST, based on tail area expansions of the marginal posterior of the parameter of interest. When in particular focus is on matching priors, further results are highlighted. Numerical illustrations are discussed.