869 resultados para Participatory mind
Resumo:
Theory of Mind (ToM) is the cognitive achievement that enables us to report our propositional attitudes, to attribute such attitudes to others, and to use such postulated or observed mental states in the prediction and explanation of behavior. Most normally developing children acquire ToM between the ages of 3 and 5 years, but serious delays beyond this chronological and mental age have been observed in children with autism, as well is in those with severe sensory impairments. We examine data from Studies of ToM in normally developing children and those with deafness, blindness, autism and Williams syndrome, as well as data from lower primates, in a search for answers to key theoretical questions concerning the origins, nature and representation of knowledge about the mind. In answer to these, we offer a framework according to which ToM is jointly dependent upon language and social experience, and is produced by a conjunction of language acquisition with children's growing social understanding, acquired through conversation and interaction with others. We argue that adequate language and adequate social skills are jointly causally sufficient, and individually causally necessary, for producing ToM. Thus our account supports a social developmental theory of the genesis of human cognition, inspired by the work of Sellars and Vygotsky.
Kindred spirits: Influences of siblings' perspectives on the child's development of a theory of mind
Resumo:
Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.
Resumo:
The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Two studies tested the hypothesis that preschool children's theory of mind ability is related to their levels of peer acceptance. In Study 1, 78 children between the ages of 4 and 6 provided peer nominations that allowed determination of social preference and social impact scores, and classification in one of five peer status groups (following Coie & Dodge, 1983). Children were also tested on five different theory of mind tasks. The results showed that theory of mind scores were significantly related to social preference scores in a subsample of children who were over 5 years old. Further, popular children were found to score higher on theory of mind tasks than children classified as rejected. Study 2 replicated and extended the first study with a new sample of 87 4- to 6-year-old children. Study 2 included measures of peer acceptance, theory of mind ability and verbal intelligence, as well as teacher ratings of prosocial and aggressive behaviours. The results of Study 2 showed that for the total group of children, prosocial behaviour was the best predictor of social preference scores. When the Study 2 sample was split into older and younger children, theory of mind ability was found to be the best predictor of social preference scores for the older children (over age 5), while aggressive and prosocial behaviours were the best predictors of peer acceptance in the younger children. Overall, the pattern of results suggests that the impact of theory of mind ability on peer acceptance is modest but increases with children's age.