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1.
Creating and disseminating knowledge through research and teaching has long been regarded as the hallmark of the modern university. However, new university business models have called into question the ‘bundling’ of teaching and research, and sustained research on the relationship between teaching and research has found little evidence of an insoluble connection between the two activities. In this article, we explore the relationship between teaching and research from the perspective of universities’ institutional discourse. We use corpus-assisted discourse analysis to examine the relationship between research and teaching as presented in two sets of institutional texts currently influential in UK Higher Education: Research Excellence Framework environment statements and Teaching Excellence Framework provider submissions (a total of 2143 documents and 12,492,071 words). Our findings show that, while universities emphasise the value of research to their teaching, they do not always emphasise (or sometimes even decry) the influence of teaching on their research. We empirically evidence that, according to what universities themselves write in institutional texts, teaching and research are not always in a mutually beneficial entanglement, but often rather a one-way relationship in which research expertise and institutional prestige are used to bolster claims of teaching excellence. This has implications for the communication of both the vision and the purpose of a university in regulatory exercises and wider policy, but also speaks to the broader idea and practice of being a university in the twenty-first century. 相似文献
2.
In recent years, the transnational movement of people has resulted in increasing tension and debates about national identity. The present research utilized a discourse analytic approach to examine accounts of national identity in the U.S. among native-born U.S. residents, Mexicans living in Mexico, and Mexicans living in the U.S. Our analysis focused on two sets of diverging accounts of national identity. A first set involved participants' explanations of national identity as natural/essential, “felt”, or conditional, which served to either constrain how “American” immigrants could be or allowed for a more inclusive definition of national identity. A second set of accounts involved participants theorizing the national polity as a multicultural or monocultural space which functioned to construct national boundaries as permeable or reinforced (White) American dominance. These patterns of talk emerged across all interviews, although U.S. participants attended to more flexible and dilemmatic (e.g. inclusionary and exclusionary) accounts of national identity. We discuss the implications for the complexity of national identity. 相似文献
3.
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
ABSTRACTThe 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
4.
基于深度学习的中文专利自动分类方法研究 总被引:2,自引:0,他引:2
[目的/意义] 面向当前国内专利审查和专利情报分析工作中对于海量专利分类的客观需求,设计了7种基于深度学习的专利自动分类方法,对比各种方法的分类效果,从而助力专利分类效率和效果的提升。[方法/过程] 针对传统机器学习方法存在的缺陷,基于Word2Vec、CNN、RNN、Attention机制等深度学习技术,考虑专利文本语序特征、上下文特征以及分类关键特征,设计Word2Vec+TextCNN、Word2Vec+GRU、Word2Vec+BiGRU、Word2Vec+BiGRU+TextCNN等7种深度学习模型,以中国专利为例,选取IPC主分类号的"部"作为分类依据,对比这7种模型与3种传统分类模型在中文专利分类任务中的效果。[结果/结论] 实证研究效果显示,采用考虑语序特征、上下文特征及强化关键特征的深度学习方法进行中文专利分类具有更优的分类效果。 相似文献
5.
[目的/意义]领域知识的跨学科交叉研究能够打破学科间的壁垒,有助于发现重大科学问题的解决方案。[研究设计/方法]基于图书情报学领域文献题录信息构建轻量级领域知识图谱,从中提取学科信息、国家信息、时间信息及其关联,采用时间与空间相结合的多维度分析方法,对学科交叉的演化进程以及国家差异进行跟踪与分析。[结论/发现]图书情报学领域内学科交叉现象日渐显著,各国家的学科交叉程度与倾向存在差异,一些目前尚不突出的交叉学科方向值得关注。[创新/价值]采用多维度视角分析学科交叉现象,相关结论可以为国家科技战略制定及学科发展规划提供有益参考。 相似文献
6.
Sally O. Hastings Trudy Milburn 《Journal of International and Intercultural Communication》2019,12(2):190-207
ABSTRACTOlfaction has been described as one of the least studied of the senses. This has certainly proven true in Communication. This project applies Ethnography of Communication and Cultural Discourse Analysis to examine the role that olfaction plays in the cultural meaning systems of two speech communities: residents surrounding the Gowanus Canal and bereaved parents. The cultural hub used to explore the cultural significance of olfaction in both speech communities is feeling. The analyses illustrate how emotions are tied to associated sensations and further become activated through radiants of dwelling, relating and acting. The analysis also shows how olfaction may serve to unify and separate members of a community. The significance of this research encourages stretching the boundaries of communication studies by examining the less studied physical senses and the boundaries of Cultural Discourse Analysis by providing distinctions that others can incorporate when examining feelings. 相似文献
7.
Child maltreatment is a complex and multifaceted construct in need of advanced statistical techniques to improve its measurement. The current study compared the predictive utility of a cumulative index to a factor analytic approach for constructing a measure of maltreatment. Data were from Waves III and IV of the National Longitudinal Study of Adolescent to Adult Health (Wave III: n = 14,800; Wave IV: n = 12,288). As adults, participants retrospectively reported on their childhood experiences of physical abuse, sexual abuse, emotional abuse, physical neglect, supervisory neglect, and social services investigations. Both the cumulative index and a two-factor solution showed evidence of convergent validity, predicting lifetime incidence of homelessness, being paid for sex, and various measures of running away or living apart from biological parents, and prospectively predicting depression, substance use, and criminal behavior. The latent variables, derived from a factor analytic approach, had greater explanatory power for many outcomes compared to the cumulative index, even when controlling for sociodemographic variables. Results suggest that factor analysis is a better methodology than a cumulative index for measuring maltreatment in large datasets when explanatory power for external outcomes is of greatest concern. 相似文献
8.
In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary. 相似文献
9.
Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean). 相似文献
10.
针对目前起重机安全评价过于依赖主观权重且忽视起重机安全状态变化趋势的问题,建立基于改进博弈论组合赋权法(improved combination weighting method of game theory,ICWGT)和灰色关联分析法的起重机安全评价体系。在该评价体系中,收集样本数据以确定评价值,构建评价等级空间来计算起重机行为特征序列与标准行为特征序列的关联系数。运用ICWGT在层次分析法和信息熵 未确知测度理论确定的主、客观权重中寻找平衡。充分考虑专家经验和样本数据,确定优化权重以改善关联系数的分配问题,从而获取起重机灰色关联度评价值和安全等级,旨在对起重机安全状态变化趋势进行更加准确的定量描述和定性分析。实例分析验证了该评价体系的有效性。 相似文献