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What is 'creolisation', and at what point do processes that might be called 'creolisation' no longer warrant the name? At what point do creole societies cease to be 'creole'? Creolisation, in the Hannerzian sense of the word, conjures up images of hybridity, globalisation, cosmopolitanism; while not a uniquely contemporary phenomenon it is nevertheless widely associated with the political and economic expansion of the European world, and the cultural implications thereof, in the colonial and post-colonial eras. On the Comorian island of Ngazidja in the western Indian Ocean, processes of social change have been the product of interactions with the outside world since first settlement of the islands some two millennia ago. Much as in neighbouring Mauritius or Réunion, but on a longer timescale, waves of immigrants have arrived on the island, interacting with the inhabitants, each other, and their external partners. They have constituted Ngazidja society and culture as 'hybrid', through processes of interaction that today—and they continue today—would be called 'creolisation'. This paper considers whether the term 'creolisation' is an appropriate and useful description of these processes or whether the widening of the term to such long-term (and perhaps less visible) processes diminishes its acuity.

Many people in the UK do not claim benefits to which they seem to be entitled. Amongst those of working-age, take-up rates for Family Credit ֠an in-work benefit available to those with children and working at least 16 hours a week ֠were the lowest of the main three means-tested benefits. In 1999, the UK Government replaced Family Credit with Working Families' Tax Credit, which was more generous, and delivered in a different way from FC. As a prelude to further work (now published as an update to this in the final report), we have analysed the decision to take up FC, and how take-up changed during the initial 6 month phase-in period of WFTC. Although there are differences in how well each records receipt of FC, we find reassuring similarities in comparable econometric models of take-up estimated on three different micro-data-sets. Entitlement, earnings, non-labour income, and education attainment are the most important determinants of FC take-up. We investigated FC take-up in greater detail using only the Family Resources Survey. Social renters are more likely to claim FC than owner occupiers or those in the private rental market, and we find that housing benefit recipients seem to under-value the potential fall in HB when considering whether to claim FC. We find that the Family Credit childcare disregard had little impact on the likelihood of take-up. Take-up of WFTC, conditional on entitlement, fell immediately after its introduction, compared to FC, but the majority of the effect is explained by the relatively low take-up rates of those families who were not previously entitled to FC. This is unsurprising, as we would not expect this group to have claimed WFTC on the first day of its existence. Work currently in progress is examining how take-up of WFTC, and the factors associated with take-up, changed between April 2000 and March 2003.

AbstractA pilot plant which has been used to examine the suitability of a number of treatment options for upgrading North West Water's water‐treatment plant at Huntingdon, Chester, is described. Processes tested include biological pretreatment using a fluidized sand bed to remove manganese and ammonia, chemical coagulation, chemical oxidation using chlorine, ozone and potassium permanganate, and both primary and secondary filtration with sand and granular activated carbon. The reduction of trihalomethanes and pesticides was also investigated.

International audience ; Understanding complex problems such as climate change is difficult for most non‐scientists, with serious implications for decision making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond with important implications for human decision making, policy support, and behaviour change. Recent research has suggested non-scientists' poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to 'run' mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual-process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model's assumptions and consequences, between the present and the future, thus potentially limiting decision making, policy support, and other behaviour changes.

International audience ; Understanding complex problems such as climate change is difficult for most non‐scientists, with serious implications for decision making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond with important implications for human decision making, policy support, and behaviour change. Recent research has suggested non-scientists' poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to 'run' mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual-process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model's assumptions and consequences, between the present and the future, thus potentially limiting decision making, policy support, and other behaviour changes.

International audience Understanding complex problems such as climate change is difficult for most non‐scientists, with serious implications for decision making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond with important implications for human decision making, policy support, and behaviour change. Recent research has suggested non-scientists' poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to 'run' mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual-process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model's assumptions and consequences, between the present and the future, thus potentially limiting decision making, policy support, and other behaviour changes.

International audience ; Understanding complex problems such as climate change is difficult for most non‐scientists, with serious implications for decision making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond with important implications for human decision making, policy support, and behaviour change. Recent research has suggested non-scientists' poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to 'run' mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual-process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model's assumptions and consequences, between the present and the future, thus potentially limiting decision making, policy support, and other behaviour changes.

By linking iterative learning and knowledge generation with power-sharing, adaptive co-management (ACM) provides a potential solution to resolving complex social-ecological problems. In this paper we evaluate ACM as a mechanism for resolving conservation conflict using a case study in Scotland, where seal and salmon fishery stakeholders have opposing and entrenched objectives. ACM emerged in 2002, successfully resolving this long-standing conflict. Applying evaluation approaches from the literature, in 2011 we interviewed stakeholders to characterise the evolution of ACM, and factors associated with its success over 10 years. In common with other ACM cases, triggers for the process were shifts in slow variables controlling the system (seal and salmon abundance, public perceptions of seal shooting), and exogenous shocks (changes in legal mandates, a seal disease outbreak). Also typical of ACM, three phases of evolution were evident: emerging local leadership preparing the system for change, a policy window of opportunity, and stakeholder partnerships building the resilience of the system. Parameters maintaining ACM were legal mechanisms and structures, legal power held by government, and the willingness of all stakeholders to reach a compromise and experiment with an alternative governance approach. Results highlighted the critical role of government power and support in resolving conservation conflict, which may constrain the extent of local stakeholder-driven ACM. The evaluation also demonstrated how, following perceived success, the trajectory of ACM has shifted to a 'stakeholder apathy' phase, with declining leadership, knowledge exchange, stakeholder engagement, and system resilience. We discuss remedial actions required to revive the process, and the importance of long term government resourcing and alternative financing schemes for successful conflict resolution. Based on the results we present a generic indicator framework and participatory method for the longitudinal evaluation of ACM applied to conservation conflict resolution.

Hospitals must have a major haemorrhage protocol in place and this should include clinical, laboratory and logistic responses.Immediate control of obvious bleeding is of paramount importance (pressure, tourniquet, haemostatic dressings).The major haemorrhage protocol must be mobilised immediately when a massive haemorrhage situation is declared.A fibrinogen 1.5 times normal represents established haemostatic failure and is predictive of microvascular bleeding. Early infusion of fresh frozen plasma (FFP; 15 ml.kg−1) should be used to prevent this occurring if a senior clinician anticipates a massive haemorrhage.Established coagulopathy will require more than 15 ml.kg−1 of FFP to correct. The most effective way to achieve fibrinogen replacement rapidly is by giving fibrinogen concentrate or cryoprecipitate if fibrinogen is unavailable.1:1:1 red cell:FFP:platelet regimens, as used by the military, are reserved for the most severely traumatised patients.A minimum target platelet count of 75 × 109.l−1 is appropriate in this clinical situation.Group-specific blood can be issued without performing an antibody screen because patients will have minimal circulating antibodies. O negative blood should only be used if blood is needed immediately.In hospitals where the need to treat massive haemorrhage is frequent, the use of locally developed shock packs may be helpful.Standard venous thromboprophylaxis should be commenced as soon as possible after haemostasis has been secured as patients develop a prothrombotic state following massive haemorrhage.

Acknowledgements We are grateful to Oana Racu (Scottish Government) and Jackie Anderson (Marine Scotland Science) for the provision of seal shooting data and salmon catch statistics, respectively. Three reviewers provided valuable comments which improved the paper. The study was conducted during the course of the authors' professional roles and without specific project funding. ; Peer reviewed ; Publisher PDF