822 resultados para Lazzard, Gilbert: Actancy. Empirical approaches to language typology


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Para profesores de primaria y todos aquellos involucrados en el diseño curricular. Aporta ideas prácticas sobre cómo el maestro puede utilizar la historia y la geografía como materias transversales para proporcionar un vehículo a través del cual los niños pueden aplicar los conocimientos y conceptos adquiridos en estas áreas. Además, los niños toman conciencia de cómo utilizar, desarrollar y ampliar los conocimientos que están adquiriendo de modo que el aprendizaje puede ser más integrado y relevante para ellos.

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Pretende conseguir dos propósitos fundamentales, el primero de ellos es favorecer una mayor reflexión y un debate fundado sobre cómo se lleva a cabo el trabajo de campo en las escuelas secundarias; y el otro, es presentar una serie de técnicas cualitativas y experienciales que puedan utilizarse en el trabajo de campo de estas escuelas.

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Resumen tomado de la publicaci??n

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Resumen basado en el de la publicaci??n

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The increasing burden of emerging infectious diseases worldwide confronts us with numerous challenges, including the imperative to design research and responses that are commensurate to understanding the complex social and ecological contexts in which infectious diseases occur. A diverse group of scientists met in Hawaii in March 2005 to discuss the linked social and ecological contexts in which infectious diseases emerge. A subset of the meeting was a group that focused on ‘‘transdisciplinary approaches’’ to integrating knowledge across and beyond academic disciplines in order to improve prevention and control of emerging infections. This article is based on the discussions of that group. Here, we outline the epidemiological legacy that has dominated infectious disease research and control up until now, and introduce the role of new, transdisciplinary and systems-based approaches to emerging infectious diseases.Wedescribe four cases of transboundary health issues and use them to discuss the potential benefits, as well as the inherent difficulties, in understanding the social–ecological contexts in which infectious diseases occur and of using transdisciplinary approaches to deal with them.

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In an immersive virtual environment, observers fail to notice the expansion of a room around them and consequently make gross errors when comparing the size of objects. This result is difficult to explain if the visual system continuously generates a 3-D model of the scene based on known baseline information from interocular separation or proprioception as the observer walks. An alternative is that observers use view-based methods to guide their actions and to represent the spatial layout of the scene. In this case, they may have an expectation of the images they will receive but be insensitive to the rate at which images arrive as they walk. We describe the way in which the eye movement strategy of animals simplifies motion processing if their goal is to move towards a desired image and discuss dorsal and ventral stream processing of moving images in that context. Although many questions about view-based approaches to scene representation remain unanswered, the solutions are likely to be highly relevant to understanding biological 3-D vision.

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This article reflects on key methodological issues emerging from children and young people's involvement in data analysis processes. We outline a pragmatic framework illustrating different approaches to engaging children, using two case studies of children's experiences of participating in data analysis. The article highlights methods of engagement and important issues such as the balance of power between adults and children, training, support, ethical considerations, time and resources. We argue that involving children in data analysis processes can have several benefits, including enabling a greater understanding of children's perspectives and helping to prioritise children's agendas in policy and practice. (C) 2007 The Author(s). Journal compilation (C) 2007 National Children's Bureau.

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This article describes an empirical, user-centred approach to explanation design. It reports three studies that investigate what patients want to know when they have been prescribed medication. The question is asked in the context of the development of a drug prescription system called OPADE. The system is aimed primarily at improving the prescribing behaviour of physicians, but will also produce written explanations for indirect users such as patients. In the first study, a large number of people were presented with a scenario about a visit to the doctor, and were asked to list the questions that they would like to ask the doctor about the prescription. On the basis of the results of the study, a categorization of question types was developed in terms of how frequently particular questions were asked. In the second and third studies a number of different explanations were generated in accordance with this categorization, and a new sample of people were presented with another scenario and were asked to rate the explanations on a number of dimensions. The results showed significant differences between the different explanations. People preferred explanations that included items corresponding to frequently asked questions in study 1. For an explanation to be considered useful, it had to include information about side effects, what the medication does, and any lifestyle changes involved. The implications of the results of the three studies are discussed in terms of the development of OPADE's explanation facility.

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In this paper we consider the estimation of population size from onesource capture–recapture data, that is, a list in which individuals can potentially be found repeatedly and where the question is how many individuals are missed by the list. As a typical example, we provide data from a drug user study in Bangkok from 2001 where the list consists of drug users who repeatedly contact treatment institutions. Drug users with 1, 2, 3, . . . contacts occur, but drug users with zero contacts are not present, requiring the size of this group to be estimated. Statistically, these data can be considered as stemming from a zero-truncated count distribution.We revisit an estimator for the population size suggested by Zelterman that is known to be robust under potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a locally truncated Poisson likelihood which is equivalent to a binomial likelihood. This result allows the extension of the Zelterman estimator by means of logistic regression to include observed heterogeneity in the form of covariates. We also review an estimator proposed by Chao and explain why we are not able to obtain similar results for this estimator. The Zelterman estimator is applied in two case studies, the first a drug user study from Bangkok, the second an illegal immigrant study in the Netherlands. Our results suggest the new estimator should be used, in particular, if substantial unobserved heterogeneity is present.

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Transgenic crops are now grown commercially on several million hectares, principally in North America. To date, the predominant crops are maize (corn), soybean, cotton, and potatoes. In addition, there have been field trials of transgenics from at least 52 species including all the major field crops, vegetables, and several herbaceous and woody species. This review summarizes recent data relating to such trials, particularly in terms of the trends away from simple, single gene traits such as herbicide and insect resistance towards more complex agronomic traits such as growth rate and increased photosynthetic efficiency. Much of the recent information is derived from inspection of patent databases, a useful source of information on commercial priorities. The review also discusses the time scale for the introduction of these transgenes into breeding populations and their eventual release as new varieties.