'A terrible danger to the morals of the country': The Irish hospitals' sweepstake in Great Britain, 1930-87

This paper examines the importance of British contributions to the success of the Irish hospitals sweepstake. In its early years, up to three-quarters of these tickets were sold in Britain, bringing millions of pounds into Ireland annually to improve and expand the state's hospitals. The vast amount of money leaving Britain in this way angered the British government and forced it to introduce new legislation to curtail the activities of the Irish sweep. The paper will highlight the extent to which the success of the sweepstake depended on the market for tickets in Britain; the threat to the sweep's survival posed by the restriction of its activities in Britain after 1935; the role of the sweepstake controversy in exacerbating further already strained relations between Britain and the Irish Free State in the 1930s; how the success of the sweep raised the issue of legalising a British lottery; and the eventual decline of the sweepstake as a force in British gambling in the post-war years.

Analysing spatio-temporal change by use of national historical Geographical Information Systems: Population change during and after the Great Irish Famine

Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change.

An Extended Implementation of the Great Deluge Algorithm for Course Timetabling

Course Scheduling consists of assigning lecture events to a limited set of specific timeslots and rooms. The objective is to satisfy as many soft constraints as possible, while maintaining a feasible solution timetable. The most successful techniques to date require a compute-intensive examination of the solution neighbourhood to direct searches to an optimum solution. Although they may require fewer neighbourhood moves than more exhaustive techniques to gain comparable results, they can take considerably longer to achieve success. This paper introduces an extended version of the Great Deluge Algorithm for the Course Timetabling problem which, while avoiding the problem of getting trapped in local optima, uses simple Neighbourhood search heuristics to obtain solutions in a relatively short amount of time. The paper presents results based on a standard set of benchmark datasets, beating over half of the currently published best results with in some cases up to 60% of an improvement.