Oral History Interview: Jo Webb

This interview is one of a series conducted with West Virginia farmers about growing up on farms and about the farming business. Mr. Webb is a West Virginia farmer who lives in Ona, Cabell County. Mr. Webb is now too old to farm and take care of himself, so his family takes care of him. The interview concerns interesting Appalachia trivia about farming and home life.https://mds.marshall.edu/oral_history/1098/thumbnail.jp

Start with the learner

This item has been published in the journal Update [©CILIP]Teaching information literacy is about empowering users, not following a sterile curriculum. To be effective, we need to provide a mixture of teaching and learning activities to accommodate diversity

‘Civic conversations’ facilitated by social media can help to reshape the relationship between citizens and local government

Amidst heated contemporary policy debates about the shifting roles and responsibilities of local government and citizen-local state relations, it is timely to ask if social media platforms such as Facebook and Twitter afford opportunities for new forms of interaction. Nick Ellison and Jo Orchard-Webb explore the idea of ‘civic conversations’ as a means of understanding the potential role that social media might play in re-shaping localized political/civic engagement between citizens and local authorities

A destination or a place of last resort? : the research library of the future, its users and its librarians

This speculative and reflective article is based on themes discussed within the literature, interviews with researchers and our own thoughts, developed during our research for a book (Webb et al., 2007) and our experience as practitioners. Themes explored include research spaces, marketing, eResearch and Library 2.0, users of the future, research support and the future role of the librarian

Bayesian integration of isotope ratio for geographic sourcing of castor beans

pre-printRecent years have seen an increase in the forensic interest associated with the poison ricin, which is extracted from the seeds of the Ricinus communis plant. Both light element (C, N, O, and H) and strontium (Sr) isotope ratios have previously been used to associate organic material with geographic regions of origin. We present a Bayesian integration methodology that can more accurately predict the region of origin for a castor bean than individual models developed independently for light element stable isotopes or Sr isotope ratios. Our results demonstrate a clear improvement in the ability to correctly classify regions based on the integrated model with a class accuracy of 60.9 ± 2.1% versus 55.9 ± 2.1% and 40.2 ± 1.8% for the light element and strontium (Sr) isotope ratios, respectively. In addition, we show graphically the strengths and weaknesses of each dataset in respect to class prediction and how the integration of these datasets strengthens the overall model