晚清留日回族学生与辛亥革命——基于“留东清真教育会”会员史迹的考察

在中国伊斯兰教和回族历史中,留东清真教育会的组建及其刊物《醒回篇》的发行,以及其爱国爱教的思想颇受后世关注,但其成员与辛亥革命的关系一直没有得到深入的研究和讨论。本文考订留东清真教育会主要成员事迹,探析其与同盟会的关系,发掘其成员归国后在各省光复运动中的表现,揭示晚清回族留日学生与辛亥革命的关联,认为该会是受孙中山民主革命思想的影响创立的一个革命团体。留东清真教育会成员的行动,体现了近代回族的文化自觉和国家认同,从一个侧面反映出民主共和观念对多民族国家少数民族发展的影响。     

基于股价预测的泛证券投资组合策略

本文基于期望效用最大化和L₁-中位数估计研究了在线投资组合选择问题。与EG（Exponential Gradient）策略仅利用单期价格信息估计价格趋势不同,本文将利用多期价格信息估计价格趋势,以提高在线策略的性能。首先,基于多期价格数据,利用L₁-中位数估计得到预期价格趋势。然后,通过期望效用最大化,提出一个新的具有线型时间复杂度的在线策略,EGLM（Exponential Gradient via L₁-Median）。并通过相对熵函数定义资产权重向量的距离,进而证明了EGLM策略具有泛证券投资组合性质。最后,利用国内外6个证券市场的历史数据进行实证分析,结果表明相较于UP（Universal Portfolio）策略和EG策略,EGLM策略有更好的竞争性能。     

高频数据瞬时波动率核估计的窗宽选择及算法研究

在瞬时波动率的各种估计量中,非参数估计量因其能准确地度量瞬时波动率,一直是学者们的研究热点。然而,这类估计量在实际应用中都面临着最优窗宽的确定问题。由于最优窗宽中往往携带一些难以估计的未知参数,使得在实际应用过程中确定最优窗宽的具体数值存在困难。本文以瞬时波动率的核估计量为例,借鉴非参数回归分析中窗宽选择的思想,构建了一种能从数据中准确计算出最优窗宽具体值的算法。理论的分析和数值上的验证表明：文中所构建的算法具有良好的稳定性、适应性和收敛速度。算法的提出为瞬时波动率的后续应用研究铺平道路。     

How leader role identity influences the process of leader emergence: A social network analysis

Contemporary theories on leadership development emphasize the importance of having a leader identity in building leadership skills and functioning effectively as leaders. We build on this approach by unpacking the role leader identity plays in the leader emergence process. Taking the perspective that leadership is a dynamic social process between group members, we propose a social network-based process model whereby leader role identity predicts network centrality (i.e., betweenness and indegree), which then contributes to leader emergence. We test our model using a sample of 88 cadets participating in a leadership development training course. In support of our model, cadets who possess a stronger leader role identity at the beginning of the course were more likely to emerge as leaders. However this relationship was only mediated by one form of network centrality, indegree centrality, reflecting one's ability to build relationships within one's group. Implications for research and practice are discussed.     

Capturing hearts and minds: The influence of relational identification with the leader on followers' mobilization and cardiovascular reactivity

The influence of relational identification (RI) on leadership processes and the effects of social identity leadership on followers' responses to stress have received scant theoretical and research attention. The present research advances theoretical understanding by testing the assertion that high RI with the leader drives follower mobilization of effort and psychophysiological responses to stress. Two experimental scenario studies (Study 1 and Study 2) support the hypothesis that being led by an individual with whom followers perceive high RI increases follower intentional mobilization. Study 2 additionally showed that high (vs. low) RI increases follower resource appraisals and cognitive task performance. A laboratory experiment (Study 3) assessing cardiovascular (CV) reactivity showed that, compared to neutral (i.e., non-affiliated) leadership, being led by an individual with whom participants felt low RI elicited a maladaptive (i.e., threat) response to a pressurized task. In addition, relative to the low RI and neutral conditions, high RI with the leader did not engender greater challenge or threat reactivity. In conclusion, advancing social identity leadership and challenge and threat theory, findings suggest that leaders should be mindful of the deleterious effects (i.e., reduced mobilization and greater threat state) of low RI to optimize follower mobilization of effort and psychophysiological responses to stress.     

Stigmatized Identities: Too Muslim to Be American,Too American to Be Muslim

In the United States today, Muslim identity is highly stigmatized. Much of this can be attributed to an increasing climate of Islamophobia. The current study finds that some Muslim Americans are confronted with another source of stigma: other Muslims. Using interview data with 23 Muslim Americans in and around Houston, TX, this study examines the intersection of religious out‐group and in‐group stigma in the lives of Muslim Americans. Findings suggest that stigma comes not only from non‐Muslims, but also from other Muslims. Some Muslim Americans are especially vulnerable to religious in‐group stigma. Those who are most acculturated to non‐Muslim, Western culture often face criticism from Muslim communities, be they inside or outside the United States. These Muslim Americans find that they are not perceived as fully Muslim or fully American, and therefore denied the full benefits of either status while simultaneously bearing the burden of both. This paper articulates the multiple dimensions of stigma faced by Muslims in America.     

Unravelling Memories of Family Separation Among Sri Lankan Tamils Resettled in Australia, 1983–2000

Abstract

Using life story interviews with 10 Sri Lankan Tamil refugees resettled in Australia, this article shows how family separation in experiences of civil war and resettlement produce long-lasting and emotional memories of fear and determination. The findings explore how young Tamil people gave meaning to family when they interacted with key individuals and negotiated cultural practices in different spaces. Moreover, intergenerational family narratives emerged as a key practice through which Tamils preserved the family identity. The analysis demonstrates how and when family separation can manifest in personal memories to reveal stories of agency and resilience. A critical engagement of the past can help to better understand concepts of childhood in relation to family and family separation in war affected diaspora communities.     

Rendering sexism invisible in workplace narratives. A narrative analysis of female entrepreneurs’ stories of not being talked to by men

Entrepreneurism is widely regarded as being one way in which women can sidestep the sexism of male‐dominated institutionalized work environments and enter into a world in which men and women operate on a level playing field. Yet, in a corpus of stories of female entrepreneurs’ experiences, we noted that being ignored by men was a constant theme. Taking a social constructionist and narrative approach to identity, we analyse the gendered identity work that female entrepreneurs do in these stories and we seek to explicate the process through which female entrepreneurs do not evaluate being ignored by men as sexism‐in‐action. Using positioning theory as an analytical tool, we analyse these stories at three different levels: the here‐and‐now interaction between interviewer and storyteller; the there‐and‐then identity work of the characters in the storyworld; and the wider societal Discourses that the storytellers enact, and which are enacted by such identity work. Findings indicate that despite making gendered difference, inferiority and lack of agency relevant, the stories are not evaluated as sexism‐in‐action because the female entrepreneurs enact a postfeminist and neoliberal Discourse of freedom, autonomy and choice, rather than a feminist Discourse of discrimination and sexism.     

ESTIMATING A PARAMETER WHEN IT IS KNOWN THAT THE PARAMETER EXCEEDS A GIVEN VALUE

In some statistical problems a degree of explicit, prior information is available about the value taken by the parameter of interest, θ say, although the information is much less than would be needed to place a prior density on the parameter's distribution. Often the prior information takes the form of a simple bound, ‘θ > θ₁ ’ or ‘θ < θ₁ ’, where θ₁ is determined by physical considerations or mathematical theory, such as positivity of a variance. A conventional approach to accommodating the requirement that θ > θ₁ is to replace an estimator, , of θ by the maximum of and θ₁. However, this technique is generally inadequate. For one thing, it does not respect the strictness of the inequality θ > θ₁ , which can be critical in interpreting results. For another, it produces an estimator that does not respond in a natural way to perturbations of the data. In this paper we suggest an alternative approach, in which bootstrap aggregation, or bagging, is used to overcome these difficulties. Bagging gives estimators that, when subjected to the constraint θ > θ₁ , strictly exceed θ₁ except in extreme settings in which the empirical evidence strongly contradicts the constraint. Bagging also reduces estimator variability in the important case for which is close to θ₁, and more generally produces estimators that respect the constraint in a smooth, realistic fashion.     

Another look at Huber's estimator: A new minimax estimator in regression with stochastically bounded noise

Huber's estimator has had a long lasting impact, particularly on robust statistics. It is well known that under certain conditions, Huber's estimator is asymptotically minimax. A moderate generalization in rederiving Huber's estimator shows that Huber's estimator is not the only choice. We develop an alternative asymptotic minimax estimator and name it regression with stochastically bounded noise (RSBN). Simulations demonstrate that RSBN is slightly better in performance, although it is unclear how to justify such an improvement theoretically. We propose two numerical solutions: an iterative numerical solution, which is extremely easy to implement and is based on the proximal point method; and a solution by applying state-of-the-art nonlinear optimization software packages, e.g., SNOPT. Contribution: the generalization of the variational approach is interesting and should be useful in deriving other asymptotic minimax estimators in other problems.