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2009 - 4S Annual Meeting - Abstract and Session Submissions Words: 158 words || 
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1. Joyce, Kelly. "Classifying Bodies, Classifying Illness: Tracing the Creation of "Autoimmune Disease"" Paper presented at the annual meeting of the 4S Annual Meeting - Abstract and Session Submissions, Hyatt Regency Crystal City, Crystal City, VA, Oct 28, 2009 <Not Available>. 2019-06-20 <http://citation.allacademic.com/meta/p374339_index.html>
Publication Type: Paper Abstract
Review Method: Peer Reviewed
Abstract: Autoimmune disease has become a salient way of categorizing a range of diseases in the United States. Scientific research, medical publications, magazines, and popular books (see, e.g., Nakazawa’s The Autoimmune Epidemic) use the term to discuss and describe seemingly disparate illnesses such as Lupus, Multiple Sclerosis, and Crohn’s disease. This paper tracks the actors and the political and social contexts that inform both the creation of the category autoimmunity and its use to classify disease. This paper will show how the prevalence of this category is the result of decades of effort and collaboration. Scientists, advocacy organizations, popular writers, pharmaceutical companies, and journalists have all worked to promote this classification that now encompasses over 80 diseases. This paper will also trace the political effects of the category’s use, examining how its use relates to marketing and advocacy. Although the idea of autoimmune disease is increasing in visibility, there has been little systematic analysis of its formation and effects.

2007 - Midwest Political Science Association Pages: 31 pages || Words: 1629 words || 
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2. Hillard, Dustin., Purpura, Stephen. and Wilkerson, John. "An Active Learning Framework for Classifying Political Text" Paper presented at the annual meeting of the Midwest Political Science Association, Palmer House Hotel, Chicago, IL, Apr 12, 2007 <Not Available>. 2019-06-20 <http://citation.allacademic.com/meta/p199169_index.html>
Publication Type: Conference Paper/Unpublished Manuscript
Abstract: We develop a framework and tools for applying a computer‐assisted context analysis system and find that it achieves levels of accuracy comparable to humans for about 80% less effort when starting from scratch (no labeled examples). The system is presented using a case study of Congressional bill titles as a proxy for the full text of Congressional bills. We also demonstrate that the system can use information learned from previous experiments to reduce the labeling requirements still further to over 90% savings of the current human effort.

This study assumes that social scientists have a need to locate individual documents in a subject area. To support this need, "Topic classification," where documents are coded according to some organizing framework, is used to facilitate search and summarization. Our proposed framework for effectively employing machine learning methods mitigates the high costs of the standard method of topic classification - human labeling. We scientifically evaluate the efficacy and accuracy of the automated approach using a large corpus of 380,000 human-labeled events and a classification system that includes 20 major policy topics, 226 subtopics, and a demonstrably strong level of human inter-coder agreement.

2007 - SOIL AND WATER CONSERVATION SOCIETY Words: 250 words || 
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3. Kyveryga, Peter. and Blackmer, Tracy. "Characterizing and classifying variability in corn yield response to nitrogen fertilizer on the scale of the farm" Paper presented at the annual meeting of the SOIL AND WATER CONSERVATION SOCIETY, Saddlebrook Resort, Tampa, Florida, Jul 21, 2007 <Not Available>. 2019-06-20 <http://citation.allacademic.com/meta/p174124_index.html>
Publication Type: Oral Presentation
Abstract: Improving nitrogen (N) management practices for corn is important for increasing profitability and reducing the environmental pollution. The need for better N management within individual fields is also driven by the possibility to apply variable rates of N. However, there is a lack of reliable information about the magnitude and frequency of yield response to N fertilizer on the scale of individual fields and farms.

The purpose of this study was to characterize and classify spatial variability in yield response to incremental increases in N fertilizer.

Fertilizer N was applied at five rates in replicated strips that entirely covered six fields during two years. Yield responses to N were measured in 22-25 individual trials per acre in grid patterns. Distributions of yield responses to N in individual trials were used to characterize variability in yield response and calculate probability of yield response and profit to fertilizer. The yield responses were classified into response categories with different fertilizer requirements by using soil map units, soil series, apparent soil electrical conductivity, and relative elevation. Analysis showed the classification explained a relatively small percentage variability in yield response to N for a combined sample of two years.


The task of classifying variability in yield responses into different response categories was found to be difficult due to interactions of soil properties and weather. This task, however, is manageable when a group of producers are determined to collect site-specific information of yield responses to N on their farms over several years across different management practices.

2011 - International Communication Association Words: 270 words || 
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4. Mueller, Marion. "“Classifying” War Visuals: A Typology of Visual News About Armed Conflict" Paper presented at the annual meeting of the International Communication Association, TBA, Boston, MA, <Not Available>. 2019-06-20 <http://citation.allacademic.com/meta/p487317_index.html>
Publication Type: Session Paper
Abstract: This paper is presenting research from an ongoing project on “Visual – Film – Discourse”, funded by the German Federal Ministry for Education and Research (BMBF). In the paper first the “functionality” of visual news reports about war and armed conflict are scrutinized, shedding light on both the documentary function, the information function, the evidential function, but also the function for collective memory and potential traumatizing effects of these images that, oftentimes, also depict almost unimaginable atrocities. In a second step, and recurring to a previous typology of atrocity images (Müller 2005), the results of a qualitative, long-term study of visual patterns and motifs of press reporting – mainly print press, but also online press photography – will be presented, concluding with the presentation of a tentative iconological typology of war visuals which will then be related to the previously discussed functions of war visuals. By documenting, “classifying” and evaluating war visuals the big picture will reveal particular patterns and compositional properties linked to specific functionalities of the images propagating or documenting war in the 21st century. On a second level, the title plays with the dual meaning of the word “to classify/classified”, meaning (a) to attribute visuals to a certain set of meta-data categories and thus using classification criteria to describe and annotate the visuals, but also (b) to deny public access to certain types of visuals which are considered to threaten security interests, or which are not publicly shown due to ethical and psychological considerations related to potentially traumatizing effects of those visuals, and argument which is linked to Sontag’s argument in “Regarding the Pain of Others”.

2011 - Association for Education in Journalism and Mass Communication Pages: 34 pages || Words: 7769 words || 
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5. Ha, Louisa. and Yun, Gi Woong. "Measuring, Classifying and Predicting Prosumption Behavior in Social Media" Paper presented at the annual meeting of the Association for Education in Journalism and Mass Communication, Renaissance Grand & Suites Hotel, St. Louis, MO, Aug 10, 2011 Online <APPLICATION/PDF>. 2019-06-20 <http://citation.allacademic.com/meta/p520641_index.html>
Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: This paper compares college students’ and general population’s prosumption behavior in social media and proposes a set of measures of prosumption in online media settings with special emphasis on social media including a prosumption index which can be used in future studies on prosumption. We classify prosumption behavior in a quadrant of four main types along the two dimensions of production and consumption. A polarized trend of prosumption was observed.

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