At home with the war: The Great War in Victorian private life. The 2014 Augustus Wolskel lecture

This article examines the Great War in Victoria through the lens of private sentiment. It exposes not only the diversity of perspectives and sentiment surrounding the war, but also the stresses endured by Victorians trying to reconcile their commitment to the war with personal and familial needs.Their experience was dominated by a confrontation with powerful currents of anxiety over the war and their loved ones, and increasing tensions within their communities over who was bearing the greater burdens of the war. Investigating private experience of total war at home allows us to see how Victorians made as well as endured the Great War, as their communities struggled to remain cohesive, and individuals struggled to cope with its demands.

Framing ICT policies to facilitate participatory e-government

This paper examines the role of information and communication technology (ICT) policies in shaping the participatory nature of local e-government. It suggests that civic involvement through e-government practices requires a combination of direct and indirect ICT policies (Cohen, van Geenhuizen and Nijkamp, 2005). Direct policies focus on ICT infrastructure development and enhance civic adoption and use of ICTs. ICTs also support policies indirectly through data organisation, information dissemination and the provision of spaces for discourse, deliberation and contributions to decision-making processes. Drawing from policy examples from Australia and the United Kingdom (UK), this paper suggests the need to combine federal guidance with local knowledge, while using policies to support ICTs and using ICTs to support policies. Such a cohesive and integrated policy relationship between federal and local government bodies is needed if local e-government is to advance to facilitate civic engagement.

War and private sentiment in Australia during 1915

This article investigates the development of a total war mentality in Australia during the First World War. Through a study of private letters and diaries, it observes the much greater level of popular commitment to the war that emerged in the middle of 1915, and an increasing acceptance throughout that year that the expanding war had taken on a life of its own, and that it would not end suddenly or without tremendous sacrifice. By the end of 1915, Australians were showing ever greater levels of dedication to a war offering increasingly less sense of how long it might continue.

Determinants of corporate capital structure: a comparison of public and private firms

 This thesis investigates how capital structure decisions of private and public firms in the UK differ in regards to their ownership structure, information asymmetry (proxied by audit quality) and access to debt capital.

Do social capital building strategies influence the financing behavior of chinese private small and medium-sized enterprises?

© 2013 Baylor University. Using data from 65,485 Chinese private small and medium-sized enterprises over the period 2000-2006, we examine the extent to which firms can improve access to debt by adopting strategies aimed at building social capital, namely entertaining and gift giving to others in their social network, and obtaining political affiliation. We find that although entertainment and gift-giving expenditure leads to higher levels of total and short-term debt, it does not enable firms to obtain greater long-term debt. In contrast, we demonstrate that obtaining political affiliation allows firms greater access to long-term debt.

Ownership concentration and product innovation in Chinese private SMEs

Product innovation is extremely important to the growth, success, and ultimate survival of firms. Although its unique features in small and medium-sized enterprises (SMEs) have gained growing attention in the literature, there is limited knowledge as to how ownership concentration moderates the relationship between product innovation and its determinants. Based upon insights from agency and institutional theories, we examine the moderating effects of ownership concentration on the relationship between product innovation and its key determinants in Chinese SMEs, utilizing a large dataset of 43,728 Chinese firms over the period 2005-2006. We focus on examining the differences between single-owner SMEs, where there is dominant control of one family member, and multiple-owner SMEs, where principal-agent conflicts and principal-principal conflicts are more likely to occur. Our findings indicate that single-owned firms tend to convert research and development into product innovation more efficiently than firms with multiple owners, who are typically better at utilizing external sources of knowledge and human capital.

The importance of outreach programs to unblock the pipeline and broaden diversity in ICT education

There is a need for outreach programs to attract a diverse range of students to the computing discipline. The lack of qualified computing graduates to fill the growing number of computing vacancies is of concern to government and industry and there are few female students entering the computing pipeline at high school level. This paper presents three outreach programs that have the underlying assumption that students need to be reminded about the creativity and potential of computing so that it remains on the radar of their future career options. Each program instigated social and cultural change through a paradigm shift where girls moved from being ICT consumers to ICT creators. By exposing students to a wide variety of ICT activities and careers during secondary schooling, they were more likely to consider studying information systems, computer science or any other computing course at the university level. Results are presented showing student attitudinal changes as well as observed increases in enrolments at secondary school and university courses

A differentially private algorithm for location data release

The rise of mobile technologies in recent years has led to large volumes of location information, which are valuable resources for knowledge discovery such as travel patterns mining and traffic analysis. However, location dataset has been confronted with serious privacy concerns because adversaries may re-identify a user and his/her sensitivity information from these datasets with only a little background knowledge. Recently, several privacy-preserving techniques have been proposed to address the problem, but most of them lack a strict privacy notion and can hardly resist the number of possible attacks. This paper proposes a private release algorithm to randomize location dataset in a strict privacy notion, differential privacy, with the goal of preserving users’ identities and sensitive information. The algorithm aims to mask the exact locations of each user as well as the frequency that the user visits the locations with a given privacy budget. It includes three privacy-preserving operations: private location clustering shrinks the randomized domain and cluster weight perturbation hides the weights of locations, while private location selection hides the exact locations of a user. Theoretical analysis on privacy and utility confirms an improved trade-off between privacy and utility of released location data. Extensive experiments have been carried out on four real-world datasets, GeoLife, Flickr, Div400 and Instagram. The experimental results further suggest that this private release algorithm can successfully retain the utility of the datasets while preserving users’ privacy.

Differentially private random forest with high utility

Privacy-preserving data mining has become an active focus of the research community in the domains where data are sensitive and personal in nature. For example, highly sensitive digital repositories of medical or financial records offer enormous values for risk prediction and decision making. However, prediction models derived from such repositories should maintain strict privacy of individuals. We propose a novel random forest algorithm under the framework of differential privacy. Unlike previous works that strictly follow differential privacy and keep the complete data distribution approximately invariant to change in one data instance, we only keep the necessary statistics (e.g. variance of the estimate) invariant. This relaxation results in significantly higher utility. To realize our approach, we propose a novel differentially private decision tree induction algorithm and use them to create an ensemble of decision trees. We also propose feasible adversary models to infer about the attribute and class label of unknown data in presence of the knowledge of all other data. Under these adversary models, we derive bounds on the maximum number of trees that are allowed in the ensemble while maintaining privacy. We focus on binary classification problem and demonstrate our approach on four real-world datasets. Compared to the existing privacy preserving approaches we achieve significantly higher utility.

Differentially private multi-task learning

Privacy restrictions of sensitive data repositories imply that the data analysis is performed in isolation at each data source. A prime example is the isolated nature of building prognosis models from hospital data and the associated challenge of dealing with small number of samples in risk classes (e.g. suicide) while doing so. Pooling knowledge from other hospitals, through multi-task learning, can alleviate this problem. However, if knowledge is to be shared unrestricted, privacy is breached. Addressing this, we propose a novel multi-task learning method that preserves privacy of data under the strong guarantees of differential privacy. Further, we develop a novel attribute-wise noise addition scheme that significantly lifts the utility of the proposed method. We demonstrate the effectiveness of our method with a synthetic and two real datasets.

Assessing Merit Aid and Need-Based Aid At Private Institutions

Institutions provide students with full tuition merit awards through formal scholarship programs for outstanding performance in academics, leadership, community service, and athletics. This brief outlines how institutions fund and utilize merit to increase retention rates, particularly for minority and first generation students.

Abstract types and distributions in independent private value auctions

In this note, in an independent private values auction framework, I discuss the relationship between the set of types and the distribution of types. I show that any set of types, finite dimensional or not, can be extended to a larger set of types preserving incentive compatibility constraints, expected revenue and bidder’s expected utilities. Thus for example we may convexify a set of types making our model amenable to the large body of theory in economics and mathematics that relies on convexity assumptions. An interesting application of this extension procedure is to show that although revenue equivalence is not valid in general if the set of types is not convex these mechanism have underlying distinct allocation mechanism in the extension. Thus we recover in these situations the revenue equivalence.

The private memory of aggregate shocks

Em economias caracterizadas por choques agregados e privados, mostramos que a alocação ótima restrita pode depender de forma não-trivial dos choques agregados. Usando versões dos modelos de Atkeson e Lucas (1992) e Mirrlees (1971) de dois períodos, é mostrado que a alocação ótima apresenta memória com relação aos choques agregados mesmo eles sendo i.i.d. e independentes dos choques individuais, quando esses últimos choques não são totalmente persistentes. O fato de os choques terem efeitos persistentes na alocação mesmo sendo informação pública, foi primeiramente apresentado em Phelan (1994). Nossas simulações numéricas indicam que esse não é um resultado pontual: existe uma relação contínua entre persistência de tipos privados e memória do choque agregado.