984 resultados para Categorical Imperative


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It’s hard not to be somewhat cynical about the self-congratulatory ‘diversity’ at the centre of the growing calendar of art bi/tri-ennials. The –ennial has proven expedient to the global tourism circuit, keeping regional economies and a relatively moderate pool of transnational artists afloat and the Asia Pacific Triennial is no exception. The mediation of representation that is imperative to the ‘best of’ formats of these transnational art shows hinges on a categorical backwardness that can feel more than a little like a Miss World competition than a progressive art show because the little tag in parenthesis after each artist’s name seems just as politically precarious now as it did forty years ago. Despite a weighty corpus of practical and critical work to the contrary, identity politics are so intrinsic to art capitalization, for both artists and institutions, that extricating ourselves from the particular and strategic politics of identification is seemingly impossible. Not that everyone wants to of course.

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Arguing for the importance of understanding the conditions under which certain forms of the social subject become visible and viable, this chapter conceptualises the current educational focus on ‘creativity’ as a technology of governmentality that has arisen from the perceived need for governing authorities to manage and responsibilise populations for the pervasive uncertainties of the global economy. With reference to the document, Tough Choices or Tough Times, a publication of the National Center on Education and the Economy in the United States, we show how creativity has been reframed as a programmable capacity of the modern student, citizen and worker primarily because it is considered an indispensible source of enterprise and innovation. Education and family life are an integral part of this bio-politics and the ongoing ‘economisation’ of social life. Our concern is that this reductionist understanding of creativity precludes other transgressive and culturally enriching creativities that represent the infinite range of subjectivities associated with imaginative human capacity and activity. It is vital therefore that educational research renders this historical process transparent and opens spaces for more socially inclusive, sustainable and productive ways of being such as those indicated by the three respondees.

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For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

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The evolutionary advantage of humans is in our unique ability to process stories – we have highly evolved ‘narrative organs.’ Through storytelling, vicarious knowledge, even guarded knowledge, is used to help our species to survive. We learn, regardless of whether the story being told is ‘truth’ or ‘fiction.’ This article discusses how humans place themselves in stories, as both observer and participant, to create a ‘neural balance’ or sweet spot that allows them to be immersed in a story without being entirely threatened by it – and how this involvement in story is the formation of empathy – an empathy that is integral to forging a future humanity. It is through empathy, we argue, that stories have the power to save us.

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A team’s climate for innovation has been shown to be important for innovation in management and work teams. This article investigates the relationship of team climate with project team innovation and performance in research and development organizations. It is argued that the relationship between team climate and innovation will be stronger for research teams than development teams as research teams have greater scope for creating novel and innovative ideas. A sample of 193 scientists and technologists in 20 research teams and 18 development teams were measured on their team’s climate for innovation, team performance, and six indicators of innovation. Research and development teams showed similar ratings for team climate and for measures of innovation. However, the relationships between team climate and individual and team innovation were stronger for research teams than development teams. These findings are significant for fostering innovativeness and innovation in knowledge work teams.

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The context in which objects are presented influences the speed at which they are named. We employed the blocked cyclic naming paradigm and perfusion functional magnetic resonance imaging (fMRI) to investigate the mechanisms responsible for interference effects reported for thematicallyand categorically related compared to unrelated contexts. Naming objects in categorically homogeneous contexts induced a significant interference effect that accumulated from the second cycle onwards. This interference effect was associated with significant perfusion signal decreases in left middle and posterior lateral temporal cortex and the hippocampus. By contrast, thematically homogeneous contexts facilitated naming latencies significantly in the first cycle and did not differ from heterogeneous contexts thereafter, nor were they associated with any perfusion signal changes compared to heterogeneous contexts. These results are interpreted as being consistent with an account in which the interference effect both originates and has its locus at the lexical level, with an incremental learning mechanism adapting the activation levels of target lexical representations following access. We discuss the implications of these findings for accounts that assume thematic relations can be active lexical competitors or assume mandatory involvement of top-down control mechanisms in interference effects during naming.

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Studies of semantic context effects in spoken word production have typically distinguished between categorical (or taxonomic) and associative relations. However, associates tend to confound semantic features or morphological representations, such as whole-part relations and compounds (e.g., BOAT-anchor, BEE-hive). Using a picture-word interference paradigm and functional magnetic resonance imaging (fMRI), we manipulated categorical (COW-rat) and thematic (COW-pasture) TARGET-distractor relations in a balanced design, finding interference and facilitation effects on naming latencies, respectively, as well as differential patterns of brain activation compared with an unrelated distractor condition. While both types of distractor relation activated the middle portion of the left middle temporal gyrus (MTG) consistent with retrieval of conceptual or lexical representations, categorical relations involved additional activation of posterior left MTG, consistent with retrieval of a lexical cohort. Thematic relations involved additional activation of the left angular gyrus. These results converge with recent lesion evidence implicating the left inferior parietal lobe in processing thematic relations and may indicate a potential role for this region during spoken word production.

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Quasi-likelihood (QL) methods are often used to account for overdispersion in categorical data. This paper proposes a new way of constructing a QL function that stems from the conditional mean-variance relationship. Unlike traditional QL approaches to categorical data, this QL function is, in general, not a scaled version of the ordinary log-likelihood function. A simulation study is carried out to examine the performance of the proposed QL method. Fish mortality data from quantal response experiments are used for illustration.

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The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

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This study addresses the following question: How to think about ethics in a technological world? The question is treated first thematically by framing central issues in the relationship between ethics and technology. This relationship has three distinct facets: i) technological advance poses new challenges for ethics, ii) traditional ethics may become poorly applicable in a technologically transformed world, and iii) the progress in science and technology has altered the concept of rationality in ways that undermine ethical thinking itself. The thematic treatment is followed by the description and analysis of three approaches to the questions framed. First, Hans Jonas s thinking on the ontology of life and the imperative of responsibility is studied. In Jonas s analysis modern culture is found to be nihilistic because it is unable to understand organic life, to find meaning in reality, and to justify morals. At the root of nihilism Jonas finds dualism, the traditional Western way of seeing consciousness as radically separate from the material world. Jonas attempts to create a metaphysical grounding for an ethic that would take the technologically increased human powers into account and make the responsibility for future generations meaningful and justified. The second approach is Albert Borgmann s philosophy of technology that mainly assesses the ways in which technological development has affected everyday life. Borgmann admits that modern technology has liberated humans from toil, disease, danger, and sickness. Furthermore, liberal democracy, possibilities for self-realization, and many of the freedoms we now enjoy would not be possible on a large scale without technology. Borgmann, however, argues that modern technology in itself does not provide a whole and meaningful life. In fact, technological conditions are often detrimental to the good life. Integrity in life, according to him, is to be sought among things and practices that evade technoscientific objectification and commodification. Larry Hickman s Deweyan philosophy of technology is the third approach under scrutiny. Central in Hickman s thinking is a broad definition of technology that is nearly equal to Deweyan inquiry. Inquiry refers to the reflective and experiential way humans adapt to their environment by modifying their habits and beliefs. In Hickman s work, technology consists of all kinds of activities that through experimentation and/or reflection aim at improving human techniques and habits. Thus, in addition to research and development, many arts and political reforms are technological for Hickman. He argues for recasting such distinctions as fact/value, poiesis/praxis/theoria, and individual/society. Finally, Hickman does not admit a categorical difference between ethics and technology: moral values and norms need to be submitted to experiential inquiry as well as all the other notions. This study mainly argues for an interdisciplinary approach to the ethics of technology. This approach should make use of the potentialities of the research traditions in applied ethics, the philosophy of technology, and the social studies on science and technology and attempt to overcome their limitations. This study also advocates an endorsement of mid-level ethics that concentrate on the practices, institutions, and policies of temporal human life. Mid-level describes the realm between the instantaneous and individualistic micro-level and the universal and global macro level.

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In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.

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The rapid growth in the field of data mining has lead to the development of various methods for outlier detection. Though detection of outliers has been well explored in the context of numerical data, dealing with categorical data is still evolving. In this paper, we propose a two-phase algorithm for detecting outliers in categorical data based on a novel definition of outliers. In the first phase, this algorithm explores a clustering of the given data, followed by the ranking phase for determining the set of most likely outliers. The proposed algorithm is expected to perform better as it can identify different types of outliers, employing two independent ranking schemes based on the attribute value frequencies and the inherent clustering structure in the given data. Unlike some existing methods, the computational complexity of this algorithm is not affected by the number of outliers to be detected. The efficacy of this algorithm is demonstrated through experiments on various public domain categorical data sets.