Opening practice: Supporting Reproducibility and Critical Spatial Data Science

This paper reflects on a number of trends towards a more open and reproducible approach to geographic and spatial data science over recent years. In particular, it considers trends towards Big Data, and the impacts this is having on spatial data analysis and modelling. It identifies a turn in academia towards coding as a core analytic tool, and away from proprietary software tools offering ‘black boxes’ where the internal workings of the analysis are not revealed. It is argued that this closed form software is problematic and considers a number of ways in which issues identified in spatial data analysis (such as the MAUP) could be overlooked when working with closed tools, leading to problems of interpretation and possibly inappropriate actions and policies based on these. In addition, this paper considers the role that reproducible and open spatial science may play in such an approach, taking into account the issues raised. It highlights the dangers of failing to account for the geographical properties of data, now that all data are spatial (they are collected somewhere), the problems of a desire for n = all observations in data science and it identifies the need for a critical approach. This is one in which openness, transparency, sharing and reproducibility provide a mantra for defensible and robust spatial data science

Toward a History of Women Projectionists in Post-war British Cinemas

Cinema projection is usually understood to be a male-dominated occupation, with the projection box characterised as a gendered space separate from the more typically feminine front-of-house roles. Although this is a fairly accurate representation, it risks eliminating all traces of women’s labour in the projection box. Previous work by David R. Williams (1997) and Rebecca Harrison (2016) has addressed the role of women projectionists during wartime, and this article begins to excavate a hidden history of women projectionists in a peacetime context. The article uses oral testimony from two women – Florence Barton and Joan Pearson – who worked as projectionists in the mid-twentieth century. Their accounts are presented in the article as two portraits, which aim to convey a sense of the women’s everyday lives in the projection box, as well as think about implications that their stories have for our understanding of women’s roles in projection more broadly. Of particular significance to both Barton and Pearson are the relationships that they had with their male colleagues, the possibilities afforded for career progression (and the different paths taken by the women) and the nature of projection work. The women’s repeated assertions that they were expected to do the same jobs as their male counterparts form a key aspect of the interviews, which suggest there is scope for further investigation of women’s labour specifically in projection boxes and in cinemas more generally

An overview of geospatial methods used in unintentional injury epidemiology

BACKGROUND: Injuries are a leading cause of death and disability around the world. Injury incidence is often associated with socio-economic and physical environmental factors. The application of geospatial methods has been recognised as important to gain greater understanding of the complex nature of injury and the associated diverse range of geographically-diverse risk factors. Therefore, the aim of this paper is to provide an overview of geospatial methods applied in unintentional injury epidemiological studies. METHODS: Nine electronic databases were searched for papers published in 2000-2015, inclusive. Included were papers reporting unintentional injuries using geospatial methods for one or more categories of spatial epidemiological methods (mapping; clustering/cluster detection; and ecological analysis). Results describe the included injury cause categories, types of data and details relating to the applied geospatial methods. RESULTS: From over 6,000 articles, 67 studies met all inclusion criteria. The major categories of injury data reported with geospatial methods were road traffic (n = 36), falls (n = 11), burns (n = 9), drowning (n = 4), and others (n = 7). Grouped by categories, mapping was the most frequently used method, with 62 (93%) studies applying this approach independently or in conjunction with other geospatial methods. Clustering/cluster detection methods were less common, applied in 27 (40%) studies. Three studies (4%) applied spatial regression methods (one study using a conditional autoregressive model and two studies using geographically weighted regression) to examine the relationship between injury incidence (drowning, road deaths) with aggregated data in relation to explanatory factors (socio-economic and environmental). CONCLUSION: The number of studies using geospatial methods to investigate unintentional injuries has increased over recent years. While the majority of studies have focused on road traffic injuries, other injury cause categories, particularly falls and burns, have also demonstrated the application of these methods. Geospatial investigations of injury have largely been limited to mapping of data to visualise spatial structures. Use of more sophisticated approaches will help to understand a broader range of spatial risk factors, which remain under-explored when using traditional epidemiological approaches