Affective disruption: Walter Benjamin and the 'history' of Ireland's industrial schools

What role do organizations play in writing history? In this paper, I address the part played by organizations in the enactment of large-scale violence, and focus on the ways in which the resulting histories come to be written. Drawing on the case of Ireland's industrial schools, I demonstrate how such accounts can act to serve the interests of those in power, effectively silencing and marginalizing weaker people. A theoretical lens that draws on ideas from Walter Benjamin and Judith Butler is helpful in understanding this; the concept of 'affective disruption' enables an exploration of how people's experiences of organizational violence can be reclaimed from the past, and protected in a continuous remembrance. Overall, this paper contributes a new perspective on the writing of organizational histories, particularly in relation to the enactment of violence. 

Optimal Front Page Advertising

We consider a model of an on-line software market, where an intermediary distributes products from sellers to buyers. When products of sellers are vertically differentiated, an intermediary, earning a proportion of sales, has an incentive to hide the worse product on the second page, and only keep the better product on the front page: that weakens the competition, allowing the seller with the better product to charge a higher price. With heterogeneous visiting costs to the second page, the platform's revenue might improve, but the outcome will become socially suboptimal.

'Easter Rising', 1914-1918-online. International Encyclopedia of the First World War

Although a military failure, the 1916 rebellion transformed Ireland by destroying the possibility of a political settlement between Irish nationalists and the British state and by popularising a republican movement prepared to use violence to achieve independence. This essay surveys the political background to the Easter Rising, its planning, the motivations and ideology of the rebels and the battle for Dublin. It concludes by assessing the Rising’s political impact and briefly summarising historiographical interpretations and commemorative trends. It argues that the origins, conduct, impact and aftermath of the insurrection are best understood within the wider context of the First World War.

Evaluation of information extraction techniques to label extracted data from e-commerce web page

Automatically determining and assigning shared and meaningful text labels to data extracted from an e-Commerce web page is a challenging problem. An e-Commerce web page can display a list of data records, each of which can contain a combination of data items (e.g. product name and price) and explicit labels, which describe some of these data items. Recent advances in extraction techniques have made it much easier to precisely extract individual data items and labels from a web page, however, there are two open problems: 1. assigning an explicit label to a data item, and 2. determining labels for the remaining data items. Furthermore, improvements in the availability and coverage of vocabularies, especially in the context of e-Commerce web sites, means that we now have access to a bank of relevant, meaningful and shared labels which can be assigned to extracted data items. However, there is a need for a technique which will take as input a set of extracted data items and assign automatically to them the most relevant and meaningful labels from a shared vocabulary. We observe that the Information Extraction (IE) community has developed a great number of techniques which solve problems similar to our own. In this work-in-progress paper we propose our intention to theoretically and experimentally evaluate different IE techniques to ascertain which is most suitable to solve this problem.

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

Walter Heissig, Rüdiger, Schott, Die Heutige Bedeutung Oraler traditionen. IHRE Archivierung, Publikation und index-Erschießung

The book under review is the publication of 28 contributions to a workshop which has tak en place in St. Augustin, near Bonn, in November 1995. This was attended by a large number of proeminent scholars, gathered around the commonly felt concern for the need to preserve “the oral traditions of all kinds” (p. 26). The papers, written in German (11), in English (16) and in French (1), are introduced by the organisers Walter Hessig and Rüdiger Schott in both German and English.