Paying the price: consequences for children’s education in prison in a market society     

《International Journal of Educational Development》2020

This article explores consequences for children’s education in custodial institutions in a contemporary market society, England and Wales. It finds that policy decision-making designed to ‘transform’ prison education for children is primarily influenced by a desire to limit the cost to the public purse of custodial placements. This paper argues that market values influence decision-making in the youth custody sector and shape the nature and quality of provision that children are permitted to access. The consequences associated with this include further fragmentation of prison provision for children, an imbalance in the types of custodial place made available, (with children disproportionately contained in the cheapest type of provision), geographical discrepancies and persistent high re-offending rates. The concern with the costs of custody is particularly prominent in a society subject to ‘austerity’ measures across a wide range of public services, particularly in the criminal justice sector (Ismail, 2020). However, it is inconsistent with contemporary knowledge and understanding of children in custody, their needs and their vulnerabilities. The transformation supposedly sought is unlikely to materialize while annual cost-per-child place is a dominant driving force. Instead, we need to start with an understanding of what individual support children in prison need in order to be ‘education ready’.  相似文献   

Multi-task learning based high-value patent and standard-essential patent identification model     

《Information processing & management》2023,60(3):103327

The high-value patent identification (HVPI) and the standard-essential patent identification (SEPI) are two important issues in the fields of intellectual property and the standardization, respectively. Almost all the HVPI and the SEPI are based on the single-task learning. In this paper, we unify the HVPI and the SEPI in a multi-task learning framework in consideration of the mutual reinforcement of the two tasks. In our model, we extract the patent structured features and embed the patent textual features using the pre-training model. Given these features, we explore a multi-task learning based identification model to identify the high-value patents and the standard-essential patents. We evaluate our model by comparing with two state-of-the-art models on the 5 balanced datasets and 2 imbalanced datasets. The results show our multi-task learning based model outperforms significantly these single-tasking learning based models in the measurements: precision, recall, F1 and accuracy. On the balanced datasets, the average increments of measurements are 1.3%, 1.29%, 1.28% and 1.28% respectively. On the imbalanced datasets, the average increments of measurements are 2.24%, 1.62%, 1.75% and 0.66% respectively.  相似文献   

Online portfolio management via deep reinforcement learning with high-frequency data     

《Information processing & management》2023,60(3):103247

Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior results in many sequence modeling tasks. The ability of Transformer to capture long-range dependencies and interactions makes it possible to apply it in the field of portfolio management (PM). However, the built-in quadratic complexity of the Transformer prevents its direct application to the PM task. To solve this problem, in this paper, we propose a deep reinforcement learning-based PM framework called LSRE-CAAN, with two important components: a long sequence representations extractor and a cross-asset attention network. Direct Policy Gradient is used to solve the sequential decision problem in the PM process. We conduct numerical experiments in three aspects using four different cryptocurrency datasets, and the empirical results show that our framework is more effective than both traditional and state-of-the-art (SOTA) online portfolio strategies, achieving a 6x return on the best dataset. In terms of risk metrics, our framework has an average volatility risk of 0.46 and an average maximum drawdown risk of 0.27 across the four datasets, both of which are lower than the vast majority of SOTA strategies. In addition, while the vast majority of SOTA strategies maintain a poor turnover rate of approximately greater than 50% on average, our framework enjoys a relatively low turnover rate on all datasets, efficiency analysis illustrates that our framework no longer has the quadratic dependency limitation.  相似文献   

RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification     

《Information processing & management》2023,60(2):103235

Imbalanced sample distribution is usually the main reason for the performance degradation of machine learning algorithms. Based on this, this study proposes a hybrid framework (RGAN-EL) combining generative adversarial networks and ensemble learning method to improve the classification performance of imbalanced data. Firstly, we propose a training sample selection strategy based on roulette wheel selection method to make GAN pay more attention to the class overlapping area when fitting the sample distribution. Secondly, we design two kinds of generator training loss, and propose a noise sample filtering method to improve the quality of generated samples. Then, minority class samples are oversampled using the improved RGAN to obtain a balanced training sample set. Finally, combined with the ensemble learning strategy, the final training and prediction are carried out. We conducted experiments on 41 real imbalanced data sets using two evaluation indexes: F1-score and AUC. Specifically, we compare RGAN-EL with six typical ensemble learning; RGAN is compared with three typical GAN models. The experimental results show that RGAN-EL is significantly better than the other six ensemble learning methods, and RGAN is greatly improved compared with three classical GAN models.  相似文献   

上海“体教结合”举措下竞技体育后备人才“学生-运动员”双重角色的认同、冲突与转化          下载免费PDF全文

侯爽 《体育科研》2019,(3):30-37

“体教结合”是解决当前我国竞技体育发展问题的重要途径和举措。传统的体育后备人才培养模式只重视专项体育技能的发展而忽视了文化教育的重要性，不利于个体的全面发展。“体教结合”更重视人的全面发展，体育与教育的融合，使得竞技体育人才逐渐从运动员这一单一角色向“学生-运动员”双重角色转变。研究以角色认同为切入口，探讨上海“体教结合”举措下，角色的转变对体育竞技后备人才的影响。选取上海体育学院中国乒乓球学院少年班学员作为“学生-运动员”样本，选取国家乒乓球青年队及部分省市队队员作为职业运动员样本，使用结构化心理测量工具，对比两类受访者在运动与学业上的角色认同、心理倦怠与动机变量的差异。得出：在上海“体教结合”举措下，竞技体育后备人才认同“学生-运动员”双重角色，他们在学业任务中的卷入程度更高；双重角色使运动员在运动任务与学业任务上的主观价值感存在差异，表现出双重角色之间的冲突，但对个体的整体人生规划并不冲突；双重角色之间的转化，对于“学生-运动员”的心理健康存在促进效应。  相似文献   

Reconsidering the use of video clubs for student-teachers' learning during field placement: Lessons drawn from a longitudinal multiple case study     

《Teaching and Teacher Education》2018

Although video clubs have been used to support (student) teachers' learning through reflection upon practice, less attention has been paid to their potential use for supporting changes in participants' practice over a period of time. Prior work has also largely treated (student) teachers as an undifferentiated whole that benefits in similar ways from video clubs. In this study, we problematize this assumption by drawing on three cases of student teachers to exemplify three different learning paths while participating in a video club during field placement. Reflecting on these findings, we discuss implications for differentiating the video-club approach to address different student teachers.  相似文献   

不同抗阻训练方案对T淋巴细胞亚群迁移和凋亡的影响*     

王焱源 《广州体育学院学报》2019,(3):112-117

研究旨在探讨一次不同抗阻训练方案对外周血CD4＋和CD8＋T淋巴细胞亚群迁移和凋亡的影响。通过实验法15名无训练经历的健康青年男性分别进行一次以促进肌肉肥大（H-RT组，方案：70%1RM，10RM，3组，组间间歇1.5 min）和以改善肌肉耐力（E-RT组，方案：60%1RM，15RM，3组，组间间歇1 min）为目的的抗阻训练方案。并于训练前、训练后即刻、训练后2 h和24 h利用流式细胞仪测定表面标志物CX3CR1和annexin V表达量检测CD4＋、CD8＋T淋巴细胞亚群迁移和凋亡（用阳性表达率表示）。得出以下数据：（1）CD4＋T细胞在H-RT组运动后即刻和运动后24 h，annexin V和CX3CR1阳性表达率显著性升高（P<0.05）。E-RT组annexin V阳性表达率在运动后即刻降低（P<0.05），24 h显著性升高（P<0.05）；CX3CR1阳性表达率仅在运动后即刻升高（P<0.05）。（2）CD8＋T细胞在H-RT组和E-RT组运动后即刻和运动后24 h，annexin V和CX3CR1阳性表达率均显著性升高（P<0.05）。通过对以上数据的分析，研究得出以下结论：CD4＋T淋巴细胞亚群对于急性抗阻训练的免疫反应存在运动方案依赖性。  相似文献   

两种大强度间歇训练对优秀公路自行车运动员有氧能力的影响          下载免费PDF全文

屈成刚  唐一丹 《体育科研》2019,(1):64-71

目的：比较两种大强度间歇训练手段对优秀自行车运动员有氧运动能力的影响。方法：将15名备战全国“十三运”的云南省自行车队男子运动员随机分为3组， S组训练方案采用SIT/耐力训练， H组训练方案采用HIIT/耐力训练， C组为对照组，进行传统耐力性训练；训练持续3周。训练前后进行递增负荷测试和有氧运动能力测试，测试指标包括最大摄氧量绝对值（VO2max）、最大摄氧量相对值（VO2max/kg）、每分通气量（VE）、最大心率（HRmax），并通过公式计算每搏输出量（SV），以及测试递增负荷后即刻血乳酸（BLA）、最大有氧功率（P）和40 km个人计时成绩进行了测试。结果：（1）3周训练后，S组运动员VE、HRmax、SV、VO2max、VO2max/kg、P和ITT40km均较训练前有显著性提高（P＜0.05）；H组运动员VE、VO2max/kg、ITT40km较训练前有显著性增加（P＜0.05），BLA有显著性的下降（P＜0.05）。（2）S组运动员ΔVE、ΔHRmax、ΔSV、ΔVO2max、ΔVO2max/kg、ΔBLA、ΔITT40km显著提升（P＜0.05），且优于其余两组；H组仅ΔITT40km存在明显提升（P＜0.05）。结论：间歇训练结合耐力训练对优秀公路自行车运动员的呼吸系统、有氧供能系统可产生积极的影响；而且，SIT结合耐力训练较HIIT结合耐力训练或传统耐力训练更能提高公路自行车运动员的有氧代谢能力和有氧运动能力，训练效果更佳。  相似文献   

Promoting a participatory convergence in a Spanish context: an inter-university action research project using visual narrative     

Elia Fernández-Díaz  Carlos Rodríguez-Hoyos  Adelina Calvo Salvador  Gloria Braga Blanco  Lorea Fernández-Olaskoaga  Prudencia Gutiérrez-Esteban 《Educational Action Research》2019,27(3):362-378

ABSTRACT

This article focuses on the deconstruction of an inter-university action research project that has allowed us to rethink our teaching and research, questioning the social, political and ethical dimensions of the university. Following the pre-assembly proposal to promote participatory convergence, organized within the framework of the 1^st Global Assembly for Knowledge Democracy (2017), an action research process was implemented in order to generate systematic inquiry around the current situation of the university and the need to act and rethink our commitment to promoting changes in this context. We have reflected on the meaning of democratization, rethinking the pedagogical relationship with our students and how we critically commit them to promote activism. We generated an environment where we look for the meaning of our practices by means of a visual narrative which has enabled us to weave and identify our own biography and become aware of where we are and why we act in one way or another. We have also focused on the search for the meaning of our actions in relation to the community we belong to and how to deal with the challenges of social justice, encouraging collaboration with other networks in a wider inter-university framework.  相似文献   

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws     

Edgardo Ferretti  Leticia Cagnina  Viviana Paiz  Sebastián Delle Donne  Rodrigo Zacagnini  Marcelo Errecalde 《Information processing & management》2018,54(6):1169-1181

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献