669 resultados para Categorization


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Objective: Qualitative research is increasingly valued as part of the evidence for policy and practice, but how it should be appraised is contested. Various appraisal methods, including checklists and other structured approaches, have been proposed but rarely evaluated. We aimed to compare three methods for appraising qualitative research papers that were candidates for inclusion in a systematic review of evidence on support for breast-feeding. Method: A sample of 12 research papers on support for breast-feeding was appraised by six qualitative reviewers using three appraisal methods: unprompted judgement, based on expert opinion; a UK Cabinet Office quality framework; and CASP, a Critical Appraisal Skills Programme tool. Papers were assigned, following appraisals, to 1 of 5 categories, which were dichotomized to indicate whether or not papers should be included in a systematic review. Patterns of agreement in categorization of papers were assessed quantitatively using κ statistics, and qualitatively using cross-case analysis. Results: Agreement in categorizing papers across the three methods was slight (κ =0.13; 95% CI 0.06-0.24). Structured approaches did not appear to yield higher agreement than that by unprompted judgement. Qualitative analysis revealed reviewers' dilemmas in deciding between the potential impact of findings and the quality of the research execution or reporting practice. Structured instruments appeared to make reviewers more explicit about the reasons for their judgements. Conclusions: Structured approaches may not produce greater consistency of judgements about whether to include qualitative papers in a systematic review. Future research should address how appraisals of qualitative research should be incorporated in systematic reviews. © The Royal Society of Medicine Press Ltd 2007.

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Faultline theory suggests that negative effects of team diversity are better understood by considering the influence of different dimensions of diversity in conjunction, rather than for each dimension separately. We develop and extend the social categorization analysis that lies at the heart of faultline theory to identify a factor that attenuates the negative influence of faultlines: the extent to which the team has shared objectives. The hypothesized moderating role of shared objectives received support in a study of faultlines formed by differences in gender, tenure, and functional background in 42 top management teams. The focus on top management teams has the additional benefit of providing the first test of the relationship between diversity faultlines and objective indicators of organizational performance. We discuss how these findings, and the innovative way in which we operationalized faultlines, extend faultline theory and research as well as offer guidelines to manage diversity faultlines.

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We examined whether inductive reasoning development is better characterized by accounts assuming an early category bias versus an early perceptual bias. We trained 264 children aged 3 to 9 years to categorize novel insects using a rule that directly pitted category membership against appearance. This was followed by an induction task with perceptual distractors at different levels of featural similarity. An additional 52 children were given the same training followed by an induction task with alternative stimuli. Categorization performance was consistently high, however we found a gradual transition from a perceptual bias in our youngest children to a category bias around age 6-7. In addition, children of all ages were equally distracted by higher levels of featural similarity. The transition is unlikely to be due to an increased ability to inhibit perceptual distractors. Instead, we argue that the transition is driven by a fundamental change in children’s understanding of category membership.

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We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding.

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We introduce a type of 2-tier convolutional neural network model for learning distributed paragraph representations for a special task (e.g. paragraph or short document level sentiment analysis and text topic categorization). We decompose the paragraph semantics into 3 cascaded constitutes: word representation, sentence composition and document composition. Specifically, we learn distributed word representations by a continuous bag-of-words model from a large unstructured text corpus. Then, using these word representations as pre-trained vectors, distributed task specific sentence representations are learned from a sentence level corpus with task-specific labels by the first tier of our model. Using these sentence representations as distributed paragraph representation vectors, distributed paragraph representations are learned from a paragraph-level corpus by the second tier of our model. It is evaluated on DBpedia ontology classification dataset and Amazon review dataset. Empirical results show the effectiveness of our proposed learning model for generating distributed paragraph representations.

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The experiment which is presented in this paper was designed to overcome some of the problems associated with previous research investigating the effects of social categorization and minority influence. Sixty-eight fourteen-year-old British Secondary School pupils indicated their attitudes towards a 'grant for pupils' before and after reading a text which advocated a minority position. The text was attributed as being the work of either pupils from their own school (ingroup minority) or from a school they discriminated against (outgroup minority). Responses were either made in ‘public’ (by telling subjects that other pupils would see their responses) or in ‘private’ (by subjects putting their responses into a ‘ballot box’). The results showed that on public responses ingroup minorities had more influence than outgroup minorities while there was no difference on private responses. Also, greater change occurred when responses were made in private than in public. These results are compatible with the intergroup analysis of minority influence.

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Combining the results of classifiers has shown much promise in machine learning generally. However, published work on combining text categorizers suggests that, for this particular application, improvements in performance are hard to attain. Explorative research using a simple voting system is presented and discussed in the light of a probabilistic model that was originally developed for safety critical software. It was found that typical categorization approaches produce predictions which are too similar for combining them to be effective since they tend to fail on the same records. Further experiments using two less orthodox categorizers are also presented which suggest that combining text categorizers can be successful, provided the essential element of ‘difference’ is considered.

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We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding.

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Groupware allows participants in an AEC/FM project to timely share relevant electronic project information at near real-time speed. One challenge of existing groupware tools is the varying information categorization needs of different AEC/FM project participants within the same groupware environment. This paper introduces initial results of a survey of several AEC/FM companies' project information categorizations. These initial results reveal differences in the ways AEC/FM project participants organize project information within each company. These differences will result in the need for a comprehensive information categorization solution when companies move their organized company specific project information to a project-wide repository in groupware. In the future, as a result of this research, a comprehensive project categorization scheme will be introduced which would allow participant-specific views of the AEC/FM project information to be rendered.

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Previous studies have described alterations in gene expression following spinal cord injury, but this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile strain on cultured spinal cord cells from E15 Sprague-Dawley rats. Microarray analysis of gene expression and categorization of identified genes were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. The application of cyclic tensile strain reduced the viability of cultured spinal cord cells significantly in a dose- and time-dependent manner. GO analysis identified candidate genes related to apoptosis (44) and to response to stimulus (17). KEGG analysis identified changes in the expression levels of 12 genes of the mitogen-activated protein kinase (MAPK) signaling pathway, which were confirmed to be upregulated and validated by RT-PCR analysis. Spinal cord cells undergo cell death in response to cyclic tensile strain, which were dose- and time-dependent, with upregulation of various genes, in particular of the MAPK pathway.

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The paper describes an extension of the cognitive architecture DUAL with a model of visual attention and perception. The goal of this attempt is to account for the construction and the categorization of object and scene representations derived from visual stimuli in the TextWorld microdomain. Low-level parallel computations are combined with an active serial deployment of visual attention enabling the construction of abstract symbolic representations. A limited-capacity short-term visual store holding information across attention shifts forms the core of the model interfacing between the low-level representation of the stimulus and DUAL’s semantic memory. The model is validated by comparing the results of a simulation with real data from an eye movement experiment with human subjects.

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Our research explores the possibility of categorizing webpages and webpage genre by structure or layout. Based on our results, we believe that webpage structure could play an important role, along with textual and visual keywords, in webpage categorization and searching.

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There is a proliferation of categorization schemes in the scientific literature that have mostly been developed from psychologists’ understanding of the nature of linguistic interactions. This has a led to problems in defining question types used by interviewers. Based on the principle that the overarching purpose of an interview is to elicit information and that questions can function both as actions in their own right and as vehicles for other actions, a Conversational Analysis approach was used to analyse a small number of police interviews. The analysis produced a different categorization of question types and, in particular, the conversational turns fell into two functional types: (i) Topic Initiation Questions and (ii) Topic Facilitation Questions. We argue that forensic interviewing requires a switch of focus from the ‘words’ used by interviewers in question types to the ‘function’ of conversational turns within interviews.

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To account for the double-edged nature of demographic workplace diversity (i.e,. relational demography, work group diversity, and organizational diversity) effects on social integration, performance, and well-being related variables, research has moved away from simple main effect approaches and started examining variables that moderate these effects. While there is no shortage of primary studies of the conditions under which diversity leads to positive or negative outcomes, it remains unclear which contingency factors make it work. Using the Categorization-Elaboration Model as our theoretical lens, we review variables moderating the effects of workplace diversity on social integration, performance, and well-being outcomes, focusing on factors that organizations and managers have control over (i.e., strategy, unit design, human resource, leadership, climate/culture, and individual differences). We point out avenues for future research and conclude with practical implications.

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In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The analysis of correspondence between connections established in the attribute space and existing links between concepts can be used as a test for creation of an adequate model of the observed world. Meta-PGN classifier is suggested as a possible tool for establishing these connections. Applying this approach in the field of content-based image retrieval of art paintings provides a tool for extracting specific feature combinations, which represent different sides of artists' styles, periods and movements.