Variable selection and estimation for high-dimensional spatial autoregressive models

Spatial regression models are important tools for many scientific disciplines including economics, business, and social science. In this article, we investigate postmodel selection estimators that apply least squares estimation to the model selected by penalized estimation in high-dimensional regression models with spatial autoregressive errors. We show that by separating the model selection and estimation process, the postmodel selection estimator performs at least as well as the simultaneous variable selection and estimation method in terms of the rate of convergence. Moreover, under perfect model selection, the ℓ₂ rate of convergence is the oracle rate of $\sqrt{s/n}$, compared with the convergence rate of $\text{◂√▸}\sqrt{s\log p/n}$ in the general case. Here, n is the sample size and p, s are the model dimension and number of significant covariates, respectively. We further provide the convergence rate of the estimation error in the form of $\sup$ norm, and ideally the rate can reach as fast as $\text{◂√▸}\sqrt{\log s/n}$.     

Young people,social workers and social work education: the role of digital skills

ABSTRACT

This paper addresses a key issue in the development of youth-focused social work: the role of digital skills in the relationship between young people and social workers who work with these native digital users. To this end, we analysed data from the International Digital Economy and Society Index 2019 and Eurostat. Information from the sixth European Working Conditions Survey and a survey conducted by the Social Care Institute for Excellence and the British Association of Social Workers supported the empirical analysis. The main findings reveal a gap between the level of digital skills required in the labour market and the actual level of digital skills in both young people and social workers, despite efforts by both groups to improve their skills. Initiatives to foster digital skills are therefore recommended to bridge this digital divide. Lastly, it was concluded that both groups could act as mutual drivers of digital transformation.     

Young people and the gendered and aesthetic dimensions of ‘enterprise’: stories from a ‘Rust Belt’ city

ABSTRACT

In the ‘Rust Belt’ city of Geelong in Victoria, Australia, discourses of young people’s enterprise and innovation provide a counter-narrative to the prevailing material and symbolic consequences of industrial decline, job losses, and the growing insecurity of employment and income. GT Magazine is a weekly, large circulation magazine in Geelong with a significant focus on the activities and aspirations of enterprising young people. In this paper, we examine, by utilising techniques of content analysis and discourse analysis, the particular ways in which young people’s innovation and enterprise are framed and enacted in GT Magazine. Our analysis reveals that ‘youth’ and ‘enterprise’ are, in GT Magazine, given an embodied form that is powerfully marked by aestheticised, normalised enactments of gender, class and race. In doing this work, we make productive contributions to three key themes in contemporary youth studies: new work orders and the youthful self as enterprise; the gendered and aesthetic dimensions of affective labour in these new work orders; and the emerging spatial turn to examine young people's embodied, place-based experiences of employment and enterprise. We seek to make problematic the sense that solutions to multiple disruptions and crises in capitalism and the environment are to be found in young people’s enterprise. Particularly when that enterprise is given form in ways that are aestheticised, gendered, classed, individualised and responsibilised.     

Age group differences in political activism in Malaysia

ABSTRACT

There is a dearth of studies on age-related patterns of political activism in Malaysia, specifically on young people’s patterns of political participation relative to their elders, and in relation to the rich literature that has developed in Western democracies. By analysing survey data from Wave 6 (2010–2014) of the World Values Surveys (WVS), this study aims to investigate the differences in political engagement between younger and older people in Malaysia, including new repertoires outside the mainstream politics, by addressing the question of whether young Malaysians are more active in political activities compared to older groups. The findings conform to the expected patterns in the literature that young people are less likely to participate in conventional political activities than their respective elders. However, we find no significant differences for unconventional political participation. The study further shows that demographic indicators such as the levels of education, gender and ethnic group belonging do not appear to be linked to the age gap between youth and their elders in political activism. As such, the study provides evidence that young people in Malaysia are less likely to be politically active than their elders and that this is not clearly attributable to the socio-demographic factors analysed.     

A Hitchhiker's Guide to caring for an older person before and during coronavirus‐19

Coronavirus‐19 (COVID‐19) has reconfigured working lives with astonishing velocity. Older people have suffered the worst effects of the pandemic, with governments marginalizing or overlooking their needs. Women perform the majority of care for older people, often compromising their working lives and health. Yet in academic articles their voices are often filtered or aggregated in quantitative studies. Based on a weave of personal experiences and secondary research, the article traces a path through UK forms of care and shows how the inadequate response to COVID‐19 stemmed from existing policies embedded in health and social care. COVID‐19 has severed important informal care work, rendering the vulnerable yet more exposed and carers anxious and bereft. Longitudinal research capturing the trajectory of care from the perspective of older people and their carers would lead to improved support hence gender equality.     

大数据驱动下的政府治理机制研究——基于2020年后精准扶贫领域的返贫阻断分析

大数据时代已经到来，大数据驱动下的政府治理发生何种改变，目前相关研究较少。当前政府治理的考验集中在2020年实现全面脱贫后精准扶贫领域的返贫阻断。文章以该领域为切入点，探索大数据驱动下政府治理的内在机制。研究发现：大数据背景下，政府治理能力催生出新的核心能力，即数据治理能力。数据治理能力驱动下，政府治理主体多元化有利于实现政府治理资源的宽范围、精准化动员；政府治理方式实现经验式决策向数据化决策转变，有利于实现政府资源的高效率和公平配置；政府治理客体的精准识别，有利于政府资源的精准化和最优化运用。但是客观上必须具备数据治理能力，主观上必须按照大数据驱动的要求重构政府治理体系（包括治理主体、治理方式和治理客体），才能真正实现以数据治理驱动政府治理，进而提高政府治理能力的目的。而数据治理能力客观上也加速了政府治理体系的重构，进而加快了政府治理能力的提升，并最终提高政府治理绩效。在对标大数据应用不同阶段分析常规式返贫阻断和大数据返贫阻断的不足和差距的基础上，笔者提出重构政府治理体系和提升数据治理能力等针对性建议。     

Staff and family attitudes to fences as a means of detaining people with dementia in residential aged care settings: The tension between physical and emotional safety

This study investigates staff and family attitudes towards the use of the fences that surround many aged care facilities in Australia, in the context of indefinite detention of people with dementia. This indefinite detention has been described in a report from an Australian Senate Inquiry as “a significant problem within the aged care context”, which “is often informal, unregulated and unlawful”. Five focus groups comprising direct care workers, family members, nurse unit managers and facility managers discussed the reasons for and their attitudes towards fences. The results show a tension between the provision of physical and emotional safety. This is to say that even while it is illegal to detain people with dementia against their will, and even while participants understood the negative impact of fences on the well‐being and emotional safety of people with dementia, they accepted and supported the presence of perimeter fences because they provided the perception that fences kept people with dementia physically safe. This has implications for redressing the balance between physical and emotional safety in policy and practice.     

Spectral goodness of fit for network models

We introduce a new statistic, ‘spectral goodness of fit’ (SGOF) to measure how well a network model explains the structure of the pattern of ties in an observed network. SGOF provides a measure of fit analogous to the standard R² in linear regression. Additionally, as it takes advantage of the properties of the spectrum of the graph Laplacian, it is suitable for comparing network models of diverse functional forms, including both fitted statistical models and algorithmic generative models of networks. After introducing, defining, and providing guidance for interpreting SGOF, we illustrate the properties of the statistic with a number of examples and comparisons to existing techniques. We show that such a spectral approach to assessing model fit fills gaps left by earlier methods and can be widely applied.