The Italian Academies, 1525-1700: a themed collection database, London, British Library

A database of books published by Italian Academies between 1525 and 1700. The Italian Academies Themed Collection provides a detailed searchable database for locating printed material relating to the Italian learned Academies active in Avellino, Bari, Benevento, Bologna, Brindisi, Caltanissetta, Catania, Catanzaro, Enna, L’Aquila, Lecce, Mantua, Naples, Padua, Palermo, Rome, Salerno, Siena, Syracuse, Trapani, and Venice in the period 1525-1700 and now held in the collections of the British Library.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Supporting schools in identifying and safeguarding the needs of disabled children: the challenges for data collection

Conceptualisations of disability that emphasise the contextual and cultural nature of disability and the embodiment of these within a national system of data collection present a number of challenges especially where this process is devolved to schools. The requirement for measures based on contextual and subjective experiences gives rise to particular difficulties in achieving parity in the way data is analysed and reported. This paper presents an account of the testing of a tool intended for use by schools as they collect data from parents to identify children who meet the criteria of disability established in Disability Discrimination Acts (DDAs). Data were validated through interviews with parents and teachers and observations of children and highlighted the pivotal role of the criterion of impact. The findings are set in the context of schools meeting their legal duties to identify disabled children and their support needs in a way that captures the complexity of disabled children’s school lives and provides useful and useable data.

Disability data collection for children's services

Schools need to identify disabled pupils in accordance with their Disability Equality Duty. This research assisted in the development of suitable tools to allow them to identify disabled children in accordance with the definition set out in the Disability Discrimination Act (DDA) by surveying parents and, via the use of purpose-designed activities, the children themselves.