Читать книгу Innovations in Digital Research Methods - Группа авторов - Страница 22

In this chapter, Lambert, Browne and Michaelides examine the prospects of the quantitative social sciences being in a position to exploit the power of new social data, computational resources and tools to achieve advances in statistical analysis. They review the range of statistical software packages currently available to social researchers and the factors influencing their patterns of adoption. They illustrate their review with examples of the application of statistical methods in domains such as education, health inequalities and epidemiology. They argue that the profusion of statistical tools, while having the benefit of offering choice to researchers, nevertheless raises significant barriers, both social and technical (and, indeed, socio-technical), that need to be addressed if the power of the tools is to be fully exploited by the social science research community.

Regarding social barriers, the authors note that in the UK there is a lack of capacity in statistical skills within the social research community. Regarding technical barriers, they observe that the proliferation of statistical tools has been at the cost of inter-operability and has created a situation that they describe as ‘balkanization’. This can deter researchers from using the tool most appropriate for a particular analysis – rather than the one they are most familiar with – and may also inhibit experimenting with new tools. Echoing the concerns raised by Purdam and Elliot, they also point to problems with transparency, replicability and robustness of statistical analyses using computer packages whose algorithms are not accessible to the user. Drawing on the principles of e-Research for their inspiration, Lambert et al. conclude by presenting some ways of overcoming the social and technical barriers, which they exemplify through their efforts to develop Stat-JR and eBooks, new tools for statistical analysis that promote inter-operability between analysis packages and sharing through better documentation of analysis routines.