“MacGyver-Meets-Dr. Ruth”: Science Journalism and the Material Positioning of Dr. Carla Pugh

This article examines the rhetorical consequences of foregrounding female scientists\u27 materials through an analysis of seven news articles on Dr. Carla Pugh, a surgeon who designs medical patient simulators. Journalists foreground Pugh\u27s materials by positioning her as both “MacGyver,” creatively assembling simulators from everyday objects, and “Dr. Ruth,” willingly discussing intimate parts. These positions avoid focusing on Pugh\u27s personal life or body but still ultimately gender her and her work. The MacGyver position associates Pugh with gendered activities, objects, and spaces while undermining her affiliation with the technical aspects of design. Meanwhile, the Dr. Ruth position implies Pugh\u27s knowledge comes from inherent bodily expertise, making certain scientific fields appear more natural for women

A Proposal for the Inclusion of Accessibility Criteria in the Publishing Workflow of Images in Biomedical Academic Articles

AbstractIn spite of the importance of visual content in academic publishing, biomedical articles do not offer accessible images, mainly because of the lack of text alternatives. According to a process-oriented accessibility philosophy, this article proposes the use of image-related texts, such as captions or mentions, as text alternatives of images, since they are solutions based on the current practices of authors of biomedical images. We also present two tools created to guide authors in writing comprehensive text alternatives. The aim of this proposal is to increase the opportunities of an actual application of accessibility principles within the biomedical academic publishing

A Linear Classifier Based on Entity Recognition Tools and a Statistical Approach to Method Extraction in the Protein-Protein Interaction Literature

We participated, in the Article Classification and the Interaction Method subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of the BioCreative III Challenge. For the ACT, we pursued an extensive testing of available Named Entity Recognition and dictionary tools, and used the most promising ones to extend our Variable Trigonometric Threshold linear classifier. For the IMT, we experimented with a primarily statistical approach, as opposed to employing a deeper natural language processing strategy. Finally, we also studied the benefits of integrating the method extraction approach that we have used for the IMT into the ACT pipeline. For the ACT, our linear article classifier leads to a ranking and classification performance significantly higher than all the reported submissions. For the IMT, our results are comparable to those of other systems, which took very different approaches. For the ACT, we show that the use of named entity recognition tools leads to a substantial improvement in the ranking and classification of articles relevant to protein-protein interaction. Thus, we show that our substantially expanded linear classifier is a very competitive classifier in this domain. Moreover, this classifier produces interpretable surfaces that can be understood as "rules" for human understanding of the classification. In terms of the IMT task, in contrast to other participants, our approach focused on identifying sentences that are likely to bear evidence for the application of a PPI detection method, rather than on classifying a document as relevant to a method. As BioCreative III did not perform an evaluation of the evidence provided by the system, we have conducted a separate assessment; the evaluators agree that our tool is indeed effective in detecting relevant evidence for PPI detection methods.Comment: BMC Bioinformatics. In Pres

Media(ted) fabrications: How the science-media symbiosis helped ‘sell’ cord banking

This paper considers the problematic role of the science–media symbiosis in the dissemination of misleading and emotionally manipulative information regarding services offered by CordBank, New Zealand's only umbilical cord blood banking facility. As this case study illustrates, the growing reliance of health and science reporters on the knowledge capital of medical specialists, biogenetic researchers, and scientists potentially enhances the ability of ‘expert’ sources to set the agenda for media representations of emerging medical and scientific developments, and may undermine the editorial independence of journalists and editors, many of whom in this case failed to critically evaluate deeply problematic claims regarding the current and future benefits of cord banking. Heavy reliance on established media frames of anecdotal personalization and technoboosterism also reinforced a proscience journalistic culture in which claims by key sources were uncritically reiterated and amplified, with journalistic assessments of the value of cord banking emphasizing potential benefits for individual consumers. It is argued that use of these media frames potentially detracts from due consideration of the broader social, ethical, legal, and health implications of emerging biomedical developments, along with the professional, personal, and increasingly also financial interests at stake in their public promotion, given the growing commercialization of biogenetic technologies

Intuitive querying of e-Health data repositories

At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised, detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico medical experiments. An integral part of the CLEF workbench is a tool to allow biomedical researchers and clinicians to query – in an intuitive way – the repository of patient data. This paper describes the CLEF query editing interface, which makes use of natural language generation techniques in order to alleviate some of the problems generally faced by natural language and graphical query interfaces. The query interface also incorporates an answer renderer that dynamically generates responses in both natural language text and graphics