4 resultados para Good and evil.

em Nottingham eTheses


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Public involvement in healthcare is a prominent policy in countries across the economically developed world. A growing body of academic literature has focused on public participation, often presenting dichotomies between good and bad practice: between initiatives that offer empowerment and those constrained by consumerism, or between those which rely for recruitment on self-selecting members of the public, and those including a more broad-based, statistically representative group. In this paper I discuss the apparent tensions between differing rationales for participation, relating recent discussions about the nature of representation in public involvement to parallel writings about the contribution of laypeople’s expertise and experience. In the academic literature, there is, I suggest, a thin line between democratic justifications for involvement, suggesting a representative role for involved publics, and technocratic ideas about the potential ‘expert’ contributions of particular subgroups of the public. Analysing recent policy documents on participation in healthcare in England, I seek moreover to show how contemporary policy transcends both categories, demanding complex roles of involved publics which invoke various qualities seen as important in governing the interface between state and society. I relate this to social-theoretical perspectives on the relationship between governmental authority and citizens in late-modern society.

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Ideas about the evolution of imperfect mimicry are reviewed. Their relevance to the colours patterns of hoverflies (Diptera, Syrphidae) are discussed in detail. Most if not all of the hoverflies labelled as mimetic actually are mimics. The apparently poor nature of their resemblance does not prevent them from obtaining at least some protection from suitably experienced birds. Mimicry is a dominant theme of this very large family of Diptera, with at least a quarter of all species in Europe being mimetic. Hoverfly mimics fall into three major groups according to their models, involving bumblebees, honeybees and social wasps. There are striking differences in the general levels of mimetic fidelity and relative abundances of the three groups, with accurate mimicry, low abundance and polymorphism characterizing the bumblebee mimics: more than half of all the species of bumblebee mimics are polymorphic. Mimics of social wasps tend to be poor mimics, have high relative abundance, and polymorphism is completely absent. Bumblebee models fall into a small number of Muellerian mimicry rings which are very different between the Palaearctic and Nearctic regions. Social wasps and associated models form one large Muellerian complex. Together with honeybees, these complexes probably form real clusters of forms as perceived by many birds. All three groups of syrphid mimics contain both good and poor mimics; some mimics are remarkably accurate, and have close morphological and behavioural resemblance. At least some apparently 'poor' mimetic resemblances may be much closer in birds' perception than we imagine, and more work needs to be done on this. Bumblebees are the least noxious and wasps the most noxious of the three main model groups. The basis of noxiousness is different, with bumblebees being classified as non-food, whereas honeybees and wasps are nasty-tasting and (rarely) stinging. The distribution of mimicry is exactly what would be expected from this ordering, with polymorphic and accurate forms being a key feature of mimics of the least noxious models, while highly noxious models have poor-quality mimicry. Even if the high abundance of many syrphid mimics relative to their models is a recent artefact of man-made environmental change, this does not preclude these species from being mimics. It seems unlikely that bird predation actually controls the populations of adult syrphids. Being rare relative to a model may have promoted or accelerated the evolution of perfect mimicry: theoretically this might account for the pattern of rare good mimics and abundant poor ones, but the idea is intrinsically unlikely. Many mimics seem to have hour-to-hour abundances related to those of their models, presumably as a result of behavioural convergence. We need to know much more about the psychology of birds as predators. There are at least four processes that need elucidating: (a) learning about the noxiousness of models; (b) the erasing of that learning through contact with mimics (extinction, or learned forgetting); (c) forgetting; (d) deliberate risk-taking and the physiological states that promote it. Johnston's (2002) model of the stabilization of imperfect mimicry by kin selection is unlikely to account for the colour patterns of hoverflies. Sherratt's (2002) model of the influence of multiple models potentially accounts for all the patterns of hoverfly mimicry, and is the most promising avenue for testing.

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We tested the prediction that, if hoverflies are Batesian mimics, this may extend to behavioral mimicry such that their numerical abundance at each hour of the day (the daily activity pattern) is related to the numbers of their hymenopteran models. After accounting for site, season, microclimatic responses and for general hoverfly abundance at three sites in north-west England, the residual numbers of mimics were significantly correlated positively with their models 9 times out of 17, while 16 out of 17 relationships were positive, itself a highly significant non-random pattern. Several eristaline flies showed significant relationships with honeybees even though some of them mimic wasps or bumblebees, perhaps reflecting an ancestral resemblance to honeybees. There was no evidence that good and poor mimics differed in their daily activity pattern relationships with models. However, the common mimics showed significant activity pattern relationships with their models, but the rarer mimics did not. We conclude that many hoverflies show behavioral mimicry of their hymenopteran models.

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This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we maintain a case base of information about the most successful heuristics for a range of previous timetabling problems to predict the best heuristic for the new problem in hand using the previous knowledge. Knowledge discovery techniques are used to carry out the training on the CBR system to improve the system performance on the prediction. Initial results presented in this paper are good and we conclude by discussing the con-siderable promise for future work in this area.