A framing analysis on Nepalese media portrayal of disaster events using news frames and PPRR cycle

This study seeks to understand the prevailing status of Nepalese media portrayal of natural disasters and develop a disaster management framework to improve the effectiveness and efficiency of news production through the continuum of prevention, preparedness, response and recovery (PPRR) phases of disaster management. The study is currently under progress. It is being undertaken in three phases. In phase-1, a qualitative content analysis is conducted. The news contents are categorized in frames as proposed in the 'Framing theory' and pre-defined frames. However, researcher has looked at the theories of the Press, linking to social responsibility theory as it is regarded as the major obligation of the media towards the society. Thereafter, the contents are categorized as per PPRR cycle. In Phase-2, based on the findings of content analysis, 12 in-depth interviews with journalists, disaster managers and community leaders are conducted. In phase-3, based on the findings of content analysis and in-depth interviews, a framework for effective media management of disaster are developed using thematic analysis. As the study is currently under progress hence, findings from the pilot study are elucidated. The response phase of disasters is most commonly reported in Nepal. There is relatively low coverage of preparedness and prevention. Furthermore, the responsibility frame in the news is most prevalent following human interest. Economic consequences and conflict frames are also used while reporting and vulnerability assessment has been used as an additional frame. The outcomes of this study are multifaceted: At the micro-level people will be benefited as it will enable a reduction in the loss of human lives and property through effective dissemination of information in news and other mode of media. They will be ‘well prepared for', 'able to prevent', 'respond to' and 'recover from' any natural disasters. At the meso level the media industry will be benefited and have their own 'disaster management model of news production' as an effective disaster reporting tool which will improve in media's editorial judgment and priority. At the macro-level it will assist government and other agencies to develop appropriate policies and strategies for better management of natural disasters.

Automated topometric graph generation from floor plan analysis

The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.

Adolescent writing development: Improving succinctness using the extended noun phrase

This study examined an aspect of adolescent writing development, specifically whether teaching secondary school students to use strategies to enhance succinctness in their essays changed the grammatical sophistication of their sentences. A quasi-experimental intervention was used to compare changes in syntactic complexity and lexical density between one-draft and polished essays. No link was demonstrated between the intervention and the changes. A thematic analysis of teacher interviews explored links between changes to student texts and teaching approaches. The study has implications for making syntactic complexity an explicit goal of student drafting.

Automatic ICD-10 classification of cancers from free-text death certificates

Objective Death certificates provide an invaluable source for cancer mortality statistics; however, this value can only be realised if accurate, quantitative data can be extracted from certificates – an aim hampered by both the volume and variable nature of certificates written in natural language. This paper proposes an automatic classification system for identifying cancer related causes of death from death certificates. Methods Detailed features, including terms, n-grams and SNOMED CT concepts were extracted from a collection of 447,336 death certificates. These features were used to train Support Vector Machine classifiers (one classifier for each cancer type). The classifiers were deployed in a cascaded architecture: the first level identified the presence of cancer (i.e., binary cancer/nocancer) and the second level identified the type of cancer (according to the ICD-10 classification system). A held-out test set was used to evaluate the effectiveness of the classifiers according to precision, recall and F-measure. In addition, detailed feature analysis was performed to reveal the characteristics of a successful cancer classification model. Results The system was highly effective at identifying cancer as the underlying cause of death (F-measure 0.94). The system was also effective at determining the type of cancer for common cancers (F-measure 0.7). Rare cancers, for which there was little training data, were difficult to classify accurately (F-measure 0.12). Factors influencing performance were the amount of training data and certain ambiguous cancers (e.g., those in the stomach region). The feature analysis revealed a combination of features were important for cancer type classification, with SNOMED CT concept and oncology specific morphology features proving the most valuable. Conclusion The system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates.

Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

Understanding teachers: The potential and possibility of discourse analysis

Understanding the ways in which teachers make sense of what they do and why is critical to a broader understanding of pedagogy. Historically, teachers have been understood through the thematic and content analysis of their beliefs or philosophies. In this paper, we argue that discourse analysis (DA) involves a much finer-grained analysis of the ‘lifeworlds’ of teachers and, in our view, provides a more detailed canvas from which inferences can be made. Our argument is structured in four parts. We begin by locating DA within the physical education (PE) literature and discuss what others have referred to as its relatively modest use. Following our location of DA, we outline a conceptual framework that we regard as useful, which contains six interrelated principles. We then introduce the idea of interpretive repertoires, which we consider to have particular explanatory power as well as being a sophisticated way to represent the subjectivities of PE teachers. Finally, we discuss the methodological strengths of interpretive repertoires. The paper concludes with a discussion on the theoretical and practical merits of adopting DA to analyse problems within PE.

Fighting like a girl … or a boy? An analysis of videos of violence between young girls posted on online fight websites

How young women engage in physical violence with other young women is an issue that raises specific concerns in both criminological literature and theories. Current theoretical explanations construct young women’s violence in one of two ways: young women are not physically violent at all, and adhere to an accepted performance of hegemonic femininity; or young women reject accepted performances of hegemonic femininity in favour of a masculine gendered performance to engage in violence successfully. This article draws on qualitative and quantitative data obtained from a structured observation and thematic analysis of 60 online videos featuring young women’s violent altercations. It argues that, contrary to this dichotomous construction, there appears to be a third way young women are performing violence, underpinned by masculine characteristics of aggression but upholding a hegemonic feminine gender performance. In making this argument, this article demonstrates that a more complex exploration and conceptualisation of young women’s violence, away from gendered constructs, is required for greater understanding of the issue.