575 research outputs found

    Interpretation and the Constraints on International Courts

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    This paper argues that methodologies of interpretation do not do what they promise – they do not constrain interpretation by providing neutral steps that one can follow in finding out a meaning of a text – but nevertheless do their constraining work by being part of what can be described as the legal practice

    Testing for Fictive Learning in Decision-Making Under Uncertainty

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    We conduct two experiments where subjects make a sequence of binary choices between risky and ambiguous binary lotteries. Risky lotteries are defined as lotteries where the relative frequencies of outcomes are known. Ambiguous lotteries are lotteries where the relative frequencies of outcomes are not known or may not exist. The trials in each experiment are divided into three phases: pre-treatment, treatment and post-treatment. The trials in the pre-treatment and post-treatment phases are the same. As such, the trials before and after the treatment phase are dependent, clustered matched-pairs, that we analyze with the alternating logistic regression (ALR) package in SAS. In both experiments, we reveal to each subject the outcomes of her actual and counterfactual choices in the treatment phase. The treatments differ in the complexity of the random process used to generate the relative frequencies of the payoffs of the ambiguous lotteries. In the first experiment, the probabilities can be inferred from the converging sample averages of the observed actual and counterfactual outcomes of the ambiguous lotteries. In the second experiment the sample averages do not converge. If we define fictive learning in an experiment as statistically significant changes in the responses of subjects before and after the treatment phase of an experiment, then we expect fictive learning in the first experiment, but no fictive learning in the second experiment. The surprising finding in this paper is the presence of fictive learning in the second experiment. We attribute this counterintuitive result to apophenia: “seeing meaningful patterns in meaningless or random data.” A refinement of this result is the inference from a subsequent Chi-squared test, that the effects of fictive learning in the first experiment are significantly different from the effects of fictive learning in the second experiment

    The impact of economic recession on maternal and infant mortality: lessons from history

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    <p>Abstract</p> <p>Background</p> <p>The effect of the recent world recession on population health has featured heavily in recent international meetings. Maternal health is a particular concern given that many countries were already falling short of their MDG targets for 2015.</p> <p>Methods</p> <p>We utilise 20<sup>th </sup>century time series data from 14 high and middle income countries to investigate associations between previous economic recession and boom periods on maternal and infant outcomes (1936 to 2005). A first difference logarithmic model is used to investigate the association between short run fluctuations in GDP per capita (individual incomes) and changes in health outcomes. Separate models are estimated for four separate time periods.</p> <p>Results</p> <p>The results suggest a modest but significant association between maternal and infant mortality and economic growth for early periods (1936 to 1965) but not more recent periods. Individual country data display markedly different patterns of response to economic changes. Japan and Canada were vulnerable to economic shocks in the post war period. In contrast, mortality rates in countries such as the UK and Italy and particularly the US appear little affected by economic fluctuations.</p> <p>Conclusions</p> <p>The data presented suggest that recessions do have a negative association with maternal and infant outcomes particularly in earlier stages of a country's development although the effects vary widely across different systems. Almost all of the 20 least wealthy countries have suffered a reduction of 10% or more in GDP per capita in at least one of the last five decades. The challenge for today's policy makers is the design and implementation of mechanisms that protect vulnerable populations from the effects of fluctuating national income.</p

    Mapping the drivers of parasitic weed abundance at a national scale : a new approach applied to Striga asiatica in the mid‐west of Madagascar

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    The parasitic weed genus Striga causes huge losses to crop production in sub‐Saharan Africa, estimated to be in excess of $7 billion per year. There is a paucity of reliable distribution data for Striga ; however, such data are urgently needed to understand current drivers, better target control efforts, as well as to predict future risks. To address this, we developed a methodology to enable rapid, large‐scale monitoring of Striga populations. We used this approach to uncover the factors that currently drive the abundance and distribution of Striga asiatica in Madagascar. Two long‐distance transects were established across the middle‐west region of Madagascar in which S. asiatica abundance in fields adjacent to the road was estimated. Management, crop structure and soil data were also collected. Analysis of the data suggests that crop variety, companion crop and previous crop were correlated with Striga density. A positive relationship between within‐field Striga density and the density of the nearest neighbouring fields indicates that spatial configuration and connectivity of suitable habitats is also important in determining Striga spread. Our results demonstrate that we are able to capture distribution and management data for Striga density at a landscape scale and use this to understand the ecological and agronomic drivers of abundance. The importance of crop varieties and cropping patterns is significant, as these are key socio‐economic elements of Malagasy cropping practices. Therefore, they have the potential to be promoted as readily available control options, rather than novel technologies requiring introduction

    Equal opportunities: Do shareable interfaces promote more group participation than single users displays?

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    Computers designed for single use are often appropriated suboptimally when used by small colocated groups working together. Our research investigates whether shareable interfaces–that are designed for more than one user to inter-act with–can facilitate more equitable participation in colocated group settings compared with single user displays. We present a conceptual framework that characterizes Shared Information Spaces (SISs) in terms of how they constrain and invite participation using different entry points. An experiment was conducted that compared three different SISs: a physical-digital set-up (least constrained), a multitouch tabletop (medium), and a laptop display (most constrained). Statistical analyses showed there to be little difference in participation levels between the three conditions other than a predictable lack of equity of control over the interface in the laptop condition. However, detailed qualitative analyses revealed more equitable participation took place in the physical-digital condition in terms of verbal utterances over time. Those who spoke the least contributed most to the physical design task. The findings are discussed in relation to the conceptual framework and, more generally, in terms of how to select, design, and combine different display technologies to support collaborative activities

    The global burden of viral hepatitis from 1990 to 2013: findings from the Global Burden of Disease Study 2013

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    BACKGROUND: With recent improvements in vaccines and treatments against viral hepatitis, an improved understanding of the burden of viral hepatitis is needed to inform global intervention strategies. We used data from the Global Burden of Disease (GBD) Study to estimate morbidity and mortality for acute viral hepatitis, and for cirrhosis and liver cancer caused by viral hepatitis, by age, sex, and country from 1990 to 2013. METHODS: We estimated mortality using natural history models for acute hepatitis infections and GBD's cause-of-death ensemble model for cirrhosis and liver cancer. We used meta-regression to estimate total cirrhosis and total liver cancer prevalence, as well as the proportion of cirrhosis and liver cancer attributable to each cause. We then estimated cause-specific prevalence as the product of the total prevalence and the proportion attributable to a specific cause. Disability-adjusted life-years (DALYs) were calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs). FINDINGS: Between 1990 and 2013, global viral hepatitis deaths increased from 0·89 million (95% uncertainty interval [UI] 0·86–0·94) to 1·45 million (1·38–1·54); YLLs from 31·0 million (29·6–32·6) to 41·6 million (39·1–44·7); YLDs from 0·65 million (0·45–0·89) to 0·87 million (0·61–1·18); and DALYs from 31·7 million (30·2–33·3) to 42·5 million (39·9–45·6). In 2013, viral hepatitis was the seventh (95% UI seventh to eighth) leading cause of death worldwide, compared with tenth (tenth to 12th) in 1990. INTERPRETATION: Viral hepatitis is a leading cause of death and disability worldwide. Unlike most communicable diseases, the absolute burden and relative rank of viral hepatitis increased between 1990 and 2013. The enormous health loss attributable to viral hepatitis, and the availability of effective vaccines and treatments, suggests an important opportunity to improve public health. FUNDING: Bill & Melinda Gates Foundation

    What are the basic self-monitoring components for cardiovascular risk management?

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    <p>Abstract</p> <p>Background</p> <p>Self-monitoring is increasingly recommended as a method of managing cardiovascular disease. However, the design, implementation and reproducibility of the self-monitoring interventions appear to vary considerably. We examined the interventions included in systematic reviews of self-monitoring for four clinical problems that increase cardiovascular disease risk.</p> <p>Methods</p> <p>We searched Medline and Cochrane databases for systematic reviews of self-monitoring for: heart failure, oral anticoagulation therapy, hypertension and type 2 diabetes. We extracted data using a pre-specified template for the identifiable components of the interventions for each disease. Data was also extracted on the theoretical basis of the education provided, the rationale given for the self-monitoring regime adopted and the compliance with the self-monitoring regime by the patients.</p> <p>Results</p> <p>From 52 randomized controlled trials (10,388 patients) we identified four main components in self-monitoring interventions: education, self-measurement, adjustment/adherence and contact with health professionals. Considerable variation in these components occurred across trials and conditions, and often components were poorly described. Few trials gave evidence-based rationales for the components included and self-measurement regimes adopted.</p> <p>Conclusions</p> <p>The components of self-monitoring interventions are not well defined despite current guidelines for self-monitoring in cardiovascular disease management. Few trials gave evidence-based rationales for the components included and self-measurement regimes adopted. We propose a checklist of factors to be considered in the design of self-monitoring interventions which may aid in the provision of an evidence-based rationale for each component as well as increase the reproducibility of effective interventions for clinicians and researchers.</p

    Treatment Outcome in Patients Receiving Assertive Community Treatment

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    In an observational study of severely mentally ill patients treated in assertive community treatment (ACT) teams, we investigated how treatment outcome was associated with demographic factors, clinical factors, and motivation for treatment. To determine psychosocial outcome, patients were routinely assessed using the Health of the Nation Outcome Scales (HoNOS). Trends over time were analyzed using a mixed model with repeated measures. The HoNOS total score was modeled as a function of treatment duration and patient-dependent covariates. Data comprised 637 assessments of 139 patients; mean duration of follow-up was 27.4 months (SD = 5.4). Substance abuse, higher age, problems with motivation, and lower educational level were associated with higher HoNOS total scores (i.e., worse outcome). To improve treatment outcome, we recommend better implementation of ACT, and also the implementation of additional programs targeting subgroups which seem to benefit less from ACT
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