Automatic Evaluation of Cancer Treatment Texts for Gist Inferences and Comprehension

Background. It is difficult to write about cancer for laypeople such that everyone understands. One common approach to readability is the Flesch-Kincaid Grade Level (FKGL). However, FKGL has been shown to be less effective than emerging discourse technologies in predicting readability. Objective. Guided by fuzzy-trace theory, we used the discourse technology Coh-Metrix to create a Gist Inference Score (GIS) and applied it to texts from the National Cancer Institute website written for patients and health care providers. We tested the prediction that patient cancer texts with higher GIS scores are likely to be better understood than others. Design. In study 1, all 244 cancer texts were systematically subjected to an automated Coh-Metrix analysis. In study 2, 9 of those patient texts (3 each at high, medium, and low GIS) were systematically converted to fill-the-blanks (Cloze) tests in which readers had to supply the missing words. Participants (162) received 3 texts, 1 at each GIS level. Measures. GIS was measured as the mean of 7 Coh-Metrix variables, and comprehension was measured through a Cloze procedure. Results. Although texts for patients scored lower on FKGL than those for providers, they also scored lower on GIS, suggesting difficulties for readers. In study 2, participants scored higher on the Cloze task for high GIS texts than for low- or medium-GIS texts. High-GIS texts seemed to better lend themselves to correct responses using different words. Limitations. GIS is limited to text and cannot assess inferences made from images. The systematic Cloze procedure worked well in aggregate but does not make fine-grained distinctions. Conclusions. GIS appears to be a useful, theoretically motivated supplement to FKGL for use in research and clinical practice.

Research Contexts

This chapter reviews the various aspects of the research contexts of doctoral research projects, namely the study environments of doctoral students, domains of discourse, technology support structures available at universities, program and department leadership support, professional and research networks, types of inter-disciplinary research, and trends in the contexts that are evident in the contemporary business environment.

Negative externalities of food production: discourses on the contested Norwegian aquaculture industry

The concern of this article is the language and ontology of negative externalities. Four discourses on the financially successful industry of salmon farming in Norway are critically analyzed and deconstructed. The discourses are: "high turnover discourse", "technology optimism discourse", "first nature discourse" and "traditionalist discourse". Groups defending various discourses differ in their interpretations of a) human/nature relations i.e. either ecocentric, anthropocentric or biocentric, and b) in their respective approach to either a transformative, adaptive or reactive logic. By linking interpretations, concepts and logic inherent to these discourses, it is possible to make conclusions on their degree of coherency. The leading discourses are maintained in language through strategic framing and overdetermination. These linguistic mechanisms are revealed in the discursive application of the concepts of sustainability and wild fish. Rather than to surrender to relativism, the article recommends integration of realism and deconstruction.Key words: Atlantic salmon farming, food production, critical discourse analysis, negative externalities, soft constructionism, parsimony, political ecology, sustainability.