高校图书馆与公共图书馆微信公众平台比较研究

[目的/意义]由于微信公众平台提升了图书馆信息传播的智能化水平，增强了图书馆服务效能，已被我国图书馆作为重要的自媒体平台广泛应用。在此背景下，针对高校图书馆与公共图书馆微信公众平台进行比较研究具有重要意义。[方法/过程]首先，利用社交媒体大数据平台和网页爬虫技术对微信公众平台推文外部描述和推文内部描述数据进行采集，数据清洗后存储在mongo DB数据库中。其次，利用微信传播指数算法计算高校图书馆与公共图书馆微信公众平台传播指数。同时，引入机器学习中的文档主题生成模型（LDA）开展这两类图书馆微信公众平台推文文本的主题分类研究。最后，提出信息收受综合指数（IA&AI）的概念与量化方法，并在设置IA&AI阈值的条件下进行基于代表性推文特征指标统计的比较研究。[结果/结论]高校图书馆与公共图书馆微信公众平台阅读数与点赞数均存在密切正相关关系；高校图书馆公众平台传播影响力较公共图书馆稍低，但这两类图书馆都存在影响力两极分化现象；比较分析后找到高校图书馆与公共图书馆推文主题异同以及较高或较低信息收受综合指数推文的信息特征差异。最后根据研究结论提出针对这两类图书馆微信公众平台运营的建议。     

气候因子对油松林蒸发散的影响

测定和分析了2006年4至10月秦岭火地塘林区油松林气候因子和净辐射的变化,采用波文比能量平衡法计算出潜热通量值,同时将潜热通量分为蒸腾通量和蒸发通量。在以上研究的基础上,利用汽化潜热进一步计算出秦岭火地塘林区油松林林地的蒸发量和油松林群落的蒸腾量。并对其与各气候因子的关系进行了主成份分析。     

报刊新闻标题中潜性语言开发手段举隅

标题用语需要变异、创新,以此来提高标题的感召力和表现力。标题语境为开发和应用潜性语言提供了条件。开发手段有开发潜句和词的潜语法功能、构造新词、开发显词潜义、特殊标题相互作用构成隐含等。使用潜性语言能使标题产生陌生化新奇感的审美效应。     

学术期刊用稿"潜规则"的危害及其对策

学术期刊在对稿件的取舍上存在着越来越多阻碍期刊健康发展的潜规则。本文阐述期刊用稿潜规则的表现形式及潜规则下作者的理性选择;分析了这些潜规则存在的原因及其危害;提出了减少这些潜规则消极作用的措施。     

企业创新开放度的多维性与关联性研究综述

开放式创新模式已成为知识经济时代企业创新战略的重要选择,如何正确认识和度量创新开放度是提升企业创新能力和创新绩效的关键之一。在对现有研究成果的理论分析基础上,本文从创新开放度的概念出发,系统归纳了创新开放度的度量方法,阐释了创新开放度构念的多维特性,认为创新开放度概念涵盖了外部创新源、组织模式、知识治理三个维度,并重点对三个维度的特点及其相互关系进行了系统分析,首次提出可将创新开放度作为潜因子型多维构念进行测度等观点,为进一步完善创新开放度的测度方法、提高测量准确度提供了新的思路,对后续的实证研究具有重要的理论启示和现实意义。     

Using a theoretical model of communal coping to understand changes in language brokers’ coping patterns: Implications for Latina/o early adolescents’ brokering stress and efficacy

Language brokering occurs when immigrant youth linguistically and culturally mediate for family and members of U.S. mainstream culture. Under some circumstances, brokering can be stressful. Based on a theoretical model of communal coping, this study utilized two waves of survey data from 342 Latina/o sixth- to eighth-grade students to identify different types of copers: (a) communal copers, (b) tentative copers, and (c) declined-ownership copers. Communal copers reported greater brokering stress than tentative brokers in the middle of the year, but not by the end of the year. Communal copers reported greater brokering efficacy than tentative copers in the middle and end of the year. Declined-ownership copers consistently had the lowest brokering stress and moderate brokering efficacy.     

现代化中的传统文化与构建社会主义和谐社会

现代化是现代性成长中从传统社会向现代社会转型的过程。它不是传统文化的断裂,而是必须发挥传统文化的现代潜能。构建社会主义和谐社会,是在社会变革中以马克思主义为指导,弘扬传统文化中公平正义、诚信友爱、自强不息、中庸和合、"天人合一"的精神,克服现代性分裂导致的矛盾冲突,走出有中国特色的社会主义现代化道路。     

Profiles of teacher-child interaction quality in preschool classrooms and teachers’ professional competence features

This paper investigates early childhood education (ECE) teachers’ self-reported and observed teacher-child interaction quality (TIQ) and the associated teachers’ professional competence features using a latent profile analysis (LPA) approach to identify the variations in the quality of classroom experiences in Chinese preschools. A total of 164 female preschool teachers aged 20–58 participated in this study. The analysis and discussions focus on four identified profiles of teachers: low-quality teachers (n = 9) characterised by lowest scores in both observational and self-reported TIQ; self-overestimated teachers (n = 59) with relatively low observed CLASS scores but high self-reported TIQ; self-underestimated teachers (n = 76) scoring relatively high in observed TIQ but low in self-assessed TIQ and low-level self-efficacy; and genuine high-quality teachers (n = 20) rated highest in both observational and self-reported TIQ. Findings on specific educational and psychological characteristics of the four profiles of teachers that we have identified through an LPA provide insights into teacher training in China.     

A Test for Measuring Teachers’ Knowledge of the Conduct and Personality of Children from Six to Eight Years of Age

Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture modeling, as well as the application to complex multilevel sampling designs. The goal of this study was to investigate—through a Monte Carlo simulation study—the performance of several methods for parameterizing multilevel latent class analysis. Of particular interest was the comparison of several such models to adequately fit Level 1 (individual) data, given a correct specification of the number of latent classes at both levels (Level 1 and Level 2). Results include the parameter estimation accuracy as well as the quality of classification at Level 1.     

Using Design-Based Latent Growth Curve Modeling With Cluster-Level Predictor to Address Dependency

The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the higher-level predictor was not included and that standard errors of the regression coefficients from the higher-level were underestimated when a regular LGCM was used. Nevertheless, random effect estimates, regression coefficients, and standard error estimates were consistent with those from the true MLGCM when the design-based LGCM included the higher-level predictor. They discussed implication for the study with empirical data illustration.