Irish social thought and the relief of poverty, 1847-1880

This paper investigates the way in which the ‘problem of poverty’ in Ireland was encountered, constructed and debated by members of the Irish intellectual and political elite in the decades between the Great Famine and the outbreak of the land war in the late 1870s. This period witnessed acute social upheavals in Ireland, from the catastrophic nadir of the Famine, through the much-vaunted economic recovery of the 1850s–1860s, to the near-famine panic of the late 1870s (itself prefigured by a lesser agricultural crisis in 1859–63). The paper focuses on how a particular elite group – the ‘Dublin School’ of political economists and their circle, and most prominently William Neilson Hancock and John Kells Ingram – sought to define and investigate the changing ‘problem’, shape public attitudes towards the legitimacy of welfare interventions and lobby state officials in the making of poor law policy in this period. It suggests that the crisis of 1859–63 played a disproportionate role in the reevaluation of Irish poor relief and in promoting a campaign for an ‘anglicisation’ of poor law measures and practice in Ireland.

River definitions in Roman technical literature

Definitions of rivers and their use by Roman land surveyors and lawyers.

Thought insertion: Abnormal sense of thought agency or thought endorsement?

The standard approach to the core phenomenology of thought insertion characterizes it in terms of a normal sense of thought ownership coupled with an abnormal sense of thought agency. Recently, Fernández (2010) has argued that there are crucial problems with this approach and has proposed instead that what goes wrong fundamentally in such a phenomenology is a sense of thought commitment, characterized in terms of thought endorsement. In this paper, we argue that even though Fernández raises new issues that enrich the topic, his proposal cannot rival the version of the standard approach we shall defend.

Technical Note: Assessing a 24/7 solution for monitoring water quality loads in small river catchments

Quantifying nutrient and sediment loads in catchments is dif?cult owing to diffuse controls related to storm hydrology. Coarse sampling and interpolation methods are prone to very high uncertainties due to under-representation of high discharge, short duration events. Additionally, important low-?ow processes such as diurnal signals linked to point source impacts are missed. Here we demonstrate a solution based on a time-integrated approach to sampling with a standard 24 bottle autosampler con?gured to take a sample every 7 h over a week according to a Plynlimon design. This is evaluated with a number of other sampling strategies using a two-year dataset of sub-hourly discharge and phosphorus concentration data. The 24/7 solution is shown to be among the least uncertain in estimating load (inter-quartile range: 96% to 110% of actual load in year 1 and 97% to 104% in year 2) due to the increased frequency raising the probability of sampling storm events and point source signals. The 24/7 solution would appear to be most parsimonious in terms of data coverage and certainty, process signal representation, potential laboratory commitment, technology requirements and the ability to be widely deployed in complex catchments.

PicSOr - An objective test of perceptual skill that predicts laparoscopic technical skill in three initial studies of laparoscopic performance

Background: Laparoscopic surgery requires surgeons to infer the shape of 3-D structures, such as the internal organs of patients, from 2-D displays on a video monitor. Recent evidence indicates that the issue is not resolved by the use of contemporary 3-D camera systems. It is therefore crucial to find ways of measuring differences in aptitude for recovering 3-D structure from 2-D images, and assessing its impact on performance. Our aim was to test empirically for a relationship between laparoscopic ability and the perceptual skill of recovering information about 3-D structures from 2-D monitor displays.