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Abstract The effect of nonfarm development on dairy farm survival in New York's highly developed lower Hudson Valley is analyzed. The major hypothesis is that significant losses of dairy farms during this period are the result of urban development pressures. Contrary to this hypothesis, however, the bivariate and multivariate analyses of data from a mail survey of all commercial dairy operators in Dutchess County as of 1984 and industry survivors, exiters, and new entrants through 1990 demonstrate that nonfarm development has a negligible effect on dairy farm survival; rather, survival is significantly affected by age of operator and by family disruption. Thus, demographic and family process factors are found to be more powerful determinants of dairy farm survival in this particular metropolitan context.  相似文献   
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This is a tutorial on the relations between population data and the rates of growth that are calculated from the data. For the calculation of rates of growth, discrete and continuous compounding will be compared so that the reader can see the reasons for using the mathematics of continuous compounding, which is the mathematics of exponential growth. Some properties of exponential growth are developed. Semi-logarithmic graphs will be discussed as a device for representing the size of growing populations and for analyzing the nature of the growth. Illustrative examples will be worked out in order to emphasize applications and utility.  相似文献   
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Summary.  Alongside the development of meta-analysis as a tool for summarizing research literature, there is renewed interest in broader forms of quantitative synthesis that are aimed at combining evidence from different study designs or evidence on multiple parameters. These have been proposed under various headings: the confidence profile method, cross-design synthesis, hierarchical models and generalized evidence synthesis. Models that are used in health technology assessment are also referred to as representing a synthesis of evidence in a mathematical structure. Here we review alternative approaches to statistical evidence synthesis, and their implications for epidemiology and medical decision-making. The methods include hierarchical models, models informed by evidence on different functions of several parameters and models incorporating both of these features. The need to check for consistency of evidence when using these powerful methods is emphasized. We develop a rationale for evidence synthesis that is based on Bayesian decision modelling and expected value of information theory, which stresses not only the need for a lack of bias in estimates of treatment effects but also a lack of bias in assessments of uncertainty. The increasing reliance of governmental bodies like the UK National Institute for Clinical Excellence on complex evidence synthesis in decision modelling is discussed.  相似文献   
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After reviewing the debate about public sociologies in the American Sociological Association over the past few years, we offer a response to calls for “saving sociology” from the Burawoy approach as well as an analytic critique of the former ASA president's “For Public Sociology” address. While being sympathetic to the basic idea of public sociologies, we argue that the “reflexive” and “critical” categories of sociology, as Burawoy has conceptualized them, are too ambiguous and value-laden to allow for empirical investigation of the different major orientations of sociological research and the ways the discipline can address non-academic audiences. Debates about the future of sociology should be undertaken with empirical evidence, and we need a theoretical approach that can allow us to compare both disciplines and nations as well as taking into account the institutional context of the universities in which we operate. Research into the conditions under which professional, critical, policy, and public sociologies could work together for the larger disciplinary and societal good is called for instead of overheated rhetoric both for and against public sociologies.  相似文献   
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Spatial variation in soil inorganic nitrogen across an arid urban ecosystem   总被引:4,自引:1,他引:3  
We explored variations in inorganic soil nitrogen (N) concentrations across metropolitan Phoenix, Arizona, and the surrounding desert using a probability-based synoptic survey. Data were examined using spatial statistics on the entire region, as well as for the desert and urban sites separately. Concentrations of both NO3-N and NH4-N were markedly higher and more heterogeneous amongst urban compared to desert soils. Regional variation in soil NO3-N concentration was best explained by latitude, land use history, population density, along with percent cover of impervious surfaces and lawn, whereas soil NH4-N concentrations were related to only latitude and population density. Within the urban area, patterns in both soil NO3-N and NH4-N were best predicted by elevation, population density and type of irrigation in the surrounding neighborhood. Spatial autocorrelation of soil NO3-N concentrations explained 49% of variation among desert sites but was absent between urban sites. We suggest that inorganic soil N concentrations are controlled by a number of ‘local’ or ‘neighborhood’ human-related drivers in the city, rather than factors related to an urban-rural gradient.  相似文献   
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