我国体育产业政策变迁:进程、逻辑及演变趋势     

徐成立  张宝雷  张月蕾  田静  陈元欣  周祖宝 《武汉体育学院学报》2020,54(3):45-53

根据政策分析研究的理论范式,通过共词分析法、聚类分析法等研究方法,分析1978—2018年国家层面的172份体育产业政策变迁的历史进程、逻辑和未来发展趋势。研究认为,我国体育产业政策历经改革开放期(1978—1992年)、积极探索期(1993—2001年)、相对停滞期(2002—2009年)、战略发展期(2010—2018年)四个阶段,并呈现阶段性特点。进而总结出我国体育产业政策变迁的历史逻辑(1)政策理念从“政府管理”到“协同治理”理念的转变;(2)政策主体从政府的“一元主体”到“多元主体”的转变;(3)政策过程从“事前控制”到“全过程”的监管;(4)政策工具从“单一运用”到“综合运用”的转变。在此基础上,提出我国体育产业政策的演变趋势(1)继续深化多元协同治理理念;(2)进一步完善政策主体多元协同机制;(3)重点强调政策过程的全过程监管;(4)提高政策工具的合理运用。  相似文献   

Childhood homelessness,resilience, and adolescent mental health: A prospective,person-centered approach     

Janette E. Herbers  J. J. Cutuli  Joanna N. Keane  Jake A. Leonard 《Psychology in the schools》2020,57(12):1830-1844

School districts and other service providers are increasingly aware of the substantial mental health needs of students experiencing family homelessness. Past findings are mixed regarding whether homelessness conveys unique risk beyond the risks associated with extreme poverty. With prospective longitudinal data on homelessness experiences across childhood, we utilized latent profile analysis as a person-centered approach to conceptualizing mental health outcomes in adolescence for 3,778 youth. We considered literal family homelessness as well as families living doubled-up, and we employed propensity score matching to identify a comparison group of nonhomeless students balanced across a range of covariates to address systematic bias. Results indicated that students who experienced literal homelessness during childhood were significantly less likely to demonstrate profiles of resilience in mental health functioning. We considered our approach and findings in light of challenges and opportunities particularly relevant to the school context.  相似文献   

Does modality matter? A latent profile and transition analysis of sedentary behaviours among school-aged youth: The UP&DOWN study     

David Sánchez-Oliva  Rebecca M. Leech  Alberto Grao-Cruces  Irene Esteban-Cornejo  Carmen Padilla-Moledo  Oscar L. Veiga 《Journal of sports sciences》2020,38(9):1062-1069

ABSTRACT

The aims of this study were to identify profiles of sedentary behaviour (SB) patterns, based on leisure-time self-reported SB modalities (screen, educative, social, and relaxing) and to evaluate changes in these profiles over 2 years among Spanish youth aged 8–18 years. Latent profile analysis (LPA), a data-driven analytic approach, was used to identify groups of boys and girls (n = 1553; 48% girls; mean±SD age: 12.56 ± 2.49 y) with distinct SB profiles using the SB modalities (time/d) as input variables. Latent transition analysis, an extension of LPA that uses longitudinal data, was used to analyse 2-year changes in these profiles. At baseline, four and three SB profiles were found among boys (labelled: screen, educative, social, and relaxing) and girls (labelled: screen/social, educative, and relaxing), respectively. Overall, more girls (range: 48%-67%) had the same profile over time, than boys (40%-52%). Participants with a screen or relaxing SB profile at baseline were more likely to have an educative profile after 2 years. Youth with a social and an educative SB profile at baseline were more likely to transition to profiles characterized by higher screen and social SB, respectively. Using a novel and person-centered approach, this study identified gender-specific SB profiles that were moderately stable over time.  相似文献   

Strengths-based reading assessment for deaf and hard-of-hearing students     

Pamela Luft 《Psychology in the schools》2020,57(3):375-393

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Assessing library topics using sentiment analysis in R: a discussion and code sample     

Brady D. Lund 《Public Services Quarterly》2020,16(2):112-123

Abstract

This article discusses the use of R programing language for executing a sentiment analysis of tweets pertaining to library topics. This discussion is situated within the literature of marketing and management sciences, which is employing methods of machine learning and business intelligence to make informed decision-making, and library administration, which has expressed great interest in social media engagement within its literature but has yet to adopt these types of analysis. Presented in this article is a sample code with instructions on how users may execute it within R to retrieve and analyze tweets relevant to library services. Two examples created using the code (analysis of top librarians’ tweets and analysis of posts about major book publishers) are used to demonstrate the functionality of the code. The code presented in this article may be used by libraries to analyze tweets about their library and library-related topics, which, in turn, may inform management and marketing design.  相似文献   

The application of inertial measurement units and functional principal component analysis to evaluate movement in the forward 3½ pike somersault springboard dive     

Cherie Walker  John Warmenhoven  Peter J. Sinclair 《Sports biomechanics / International Society of Biomechanics in Sports》2019,18(2):146-162

Based on technological and analytical advances, the capability to more accurately and finitely examine biomechanical and skill characteristics of movement has improved. The purpose of this study was to use Inertial Measurement Units (IMUs) and Functional Principal Components Analysis (fPCA) to examine the role of movement variability (assessed via angular velocity), on 2 divers (1 international level; 1 national) performing the forward 3½ pike somersault dive. Analysis of angular velocity curves during ive-flight identified 5 fPCs, accounting for 96.5% of movement variability. The national diver’s scatter plots and standard deviation of fPC scores illustrated larger magnitudes of angular velocity variability across dive flight. For fPC1 and fPC3, magnitudes of SD variability were 282.6 and 201.5, respectively. The international diver illustrated more consistent angular velocity profiles, with clustering of fPCs scores (e.g., fPC1 & 3 = SD’s of 75.2 & 68.0). To account for lower variability in the international diver, the ability to better coordinate movement sequences and functionally utilise feedback in response to initiation of the somersault position is highlighted. Overall, findings highlight how both IMUs and fPCA can more holistically and finitely examine the biomechanical and skill characteristics of movement sequences with the capability to inform athlete development.  相似文献   

基于用户兴趣度量的知识发现服务精准推荐     

丁梦晓  毕强  许鹏程  李洁  牟冬梅 《图书情报工作》2019,63(3):21-29

[目的/意义]针对当前知识发现服务中存在的个性化程度不高和推荐效果不佳等问题，提出一种基于用户兴趣度量和内容分析的推荐算法。[方法/过程]文章通过特征词分布、LDA主题分布、引文结构网络三个维度构建学术资源模型，并通过对用户行为的度量，计算用户对其浏览学术资源的兴趣度，结合学术资源模型构建用户兴趣模型。将用户兴趣模型与学术资源模型匹配，计算其相似度，得到用户对每条学术资源的兴趣值，最后将兴趣值最高的TOP-N学术资源推荐给用户。[结果/结论]通过实验检验算法的有效性和推荐准确率，结果显示，本文从实时动态度量兴趣的角度，提出的推荐算法能较好地预测用户兴趣，推荐效果显著，为实现发现服务精准推荐提供思路。  相似文献   

Writer identification approach based on bag of words with OBI features     

Amal Durou  Ibrahim Aref  Somaya Al-Maadeed  Ahmed Bouridane  Elhadj Benkhelifa 《Information processing & management》2019,56(2):354-366

Handwriter identification aims to simplify the task of forensic experts by providing them with semi-automated tools in order to enable them to narrow down the search to determine the final identification of an unknown handwritten sample. An identification algorithm aims to produce a list of predicted writers of the unknown handwritten sample ranked in terms of confidence measure metrics for use by the forensic expert will make the final decision.Most existing handwriter identification systems use either statistical or model-based approaches. To further improve the performances this paper proposes to deploy a combination of both approaches using Oriented Basic Image features and the concept of graphemes codebook. To reduce the resulting high dimensionality of the feature vector a Kernel Principal Component Analysis has been used. To gauge the effectiveness of the proposed method a performance analysis, using IAM dataset for English handwriting and ICFHR 2012 dataset for Arabic handwriting, has been carried out. The results obtained achieved an accuracy of 96% thus demonstrating its superiority when compared against similar techniques.  相似文献   

Co-occurrence of adverse childhood experiences and its association with family characteristics. A latent class analysis with Dutch population data     

《Child abuse & neglect》2019

BackgroundAlthough adverse childhood experiences (ACEs) are relatively common among children, there is limited knowledge on the co-occurrence of such experiences.ObjectiveThe current study therefore investigates co-occurrence of childhood adversity in the Netherlands and whether specific clusters are more common among certain types of families.Participants and SettingRepresentative data from the Family Survey Dutch population 2018 (N = 3,128) are employed.MethodWe estimate Latent Class Analysis (LCA) models to investigate co-occurrence of ACEs. As ACEs we examine maltreatment, household dysfunction, demographic family events, as well as financial and chronic health problems. Gradual measures for maltreatment and financial problems are studied to make it possible to differentiate with regard to the severity of experiences.ResultsOur results show that four ACE clusters may be identified: ‘Low ACE’, ‘Moderate ACE: Household dysfunction’, ‘Moderate ACE: Maltreatment’ and ‘High ACE’. Regression analyses indicated that mother’s age at first childbirth and the number of siblings were related to experiencing childhood adversity. We found limited evidence for ACEs to be related to a family’s socioeconomic position.ConclusionThe found clusters of ACEs reflect severity of childhood adversity, but also the types of adversity a child experienced. For screening and prevention of childhood adversity as well as research on its consequences, it is relevant to acknowledge this co-occurrence of types and severity of adversity.  相似文献   

Location extraction from tweets     

Thi Bich Ngoc Hoang  Josiane Mothe 《Information processing & management》2018,54(2):129-144

Five hundred million tweets are posted daily, making Twitter a major social media platform from which topical information on events can be extracted. These events are represented by three main dimensions: time, location and entity-related information. The focus of this paper is location, which is an essential dimension for geo-spatial applications, either when helping rescue operations during a disaster or when used for contextual recommendations. While the first type of application needs high recall, the second is more precision-oriented. This paper studies the recall/precision trade-off, combining different methods to extract locations. In the context of short posts, applying tools that have been developed for natural language is not sufficient given the nature of tweets which are generally too short to be linguistically correct. Also bearing in mind the high number of posts that need to be handled, we hypothesize that predicting whether a post contains a location or not could make the location extractors more focused and thus more effective. We introduce a model to predict whether a tweet contains a location or not and show that location prediction is a useful pre-processing step for location extraction. We define a number of new tweet features and we conduct an intensive evaluation. Our findings are that (1) combining existing location extraction tools is effective for precision-oriented or recall-oriented results, (2) enriching tweet representation is effective for predicting whether a tweet contains a location or not, (3) words appearing in a geography gazetteer and the occurrence of a preposition just before a proper noun are the two most important features for predicting the occurrence of a location in tweets, and (4) the accuracy of location extraction improves when it is possible to predict that there is a location in a tweet.  相似文献