428 research outputs found

    Agrarian structure in Poland : the myth of large-farm superiority

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    In Poland, present policies are aimed at promoting large, mechanized farms over smaller family farms. These policies are based on the perception that large farms offer real economies of scale. But international evidence indicates that such large, mechanized farms are generally less efficient and use less labor than small family farms. The authors analyzed the relationship between farm size and efficiency in Polish agriculture. They used two different methods to do so. First they determined differences in total factor productivity between small and large farms. They then used Data Envelope Analysis to estimate scale efficiencies. The results show that, for the sample of farms analyzed: 1) large farms are not more efficient than smaller farms; and 2) smaller farms are more labor-intensive than larger farms. These results have important policy implications for farm restructuring in Poland and other transition economies facing similar issues and conditions.Environmental Economics&Policies,Crops&Crop Management Systems,Agricultural Knowledge&Information Systems,Banks&Banking Reform,Economic Theory&Research,Banks&Banking Reform,Environmental Economics&Policies,Agricultural Knowledge&Information Systems,Crops&Crop Management Systems,Livestock&Animal Husbandry

    Blackfeet build their future

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    Language history : A tale of two countries

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    This paper looks at the relationships between industry computer languages and those taught in universities. By considering the differences between two of the first countries to embrace programmable computers (USA and Australia) we find patterns that seem culturally independent. History shows a set of recurring problems for academics in choosing languages. This study shows that academics should be informed by history when making those decisions.2nd IFIP Conference on the History of Computing and EducationRed de Universidades con Carreras en Informática (RedUNCI

    Applied Learning with the Virtual Teaching Assistant

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    The relevance of a university degree depends upon the ability of graduates to apply their learning in complex problemsolving situations. This ability should be taught and practiced wherever possible in the curriculum, but often requires asubstantial commitment of face-to-face instructor time. However, in many disciplines software systems can be constructed toprovide or supplement relevant learning environments. This paper describes a system developed through the use of the designand development research technique. The case shows how collaborative, intentional, and project-based learning can beincorporated in and stimulated by design decisions informed by the research technique. The paper provides details about asystem built around realistic role playing and supported by a range of tools. The combination of a scenario with a real-worldcontext, along with a software system that evaluates student work as well as interactively mentoring students, provides theservices of a virtual teaching assistant

    e-Government and the Elderly: A Two Country Comparison

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    This paper first identifies characteristics of aging populations across two countries: the USA and Australia. Government websites of special interest to the elderly are then identified at three levels of government: National, State and Local. A randomsample of these sites is tested for readability. Results show that reading levels of web sites are harder than thoserecommended and that this design flaw occurs across all levels of government and between the two countries. It is arguedthat the simple mistake of making material too hard for the elderly to read inhibits the transformative ability of e-governmentfor this citizen group with special needs

    Retirement Plans, Attitudes, and Expectations of Kansas Board of Regents Faculty

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    This data set enables the examination of investment choices of a mature group of faculty, where saving for retirement is a major investment objective. Consideration of future retirement-related policy proposals by universities should be evaluated with an understanding of the relative importance of economic and non-economic influences upon the retirement decision by university faculty.https://scholars.fhsu.edu/fort_hays_studies_series/1017/thumbnail.jp

    Evaluation Framework for Water Quality Trading Programs in the Chesapeake Bay Watershed

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    Water quality trading programs are being proposed and implemented across the US in a variety of forms and with differing objectives. The programs being proposed and implemented in the Chesapeake Bay region are no exception. Against this background the Chesapeake Bay Program's Scientific and Technical Advisory Committee and the Mid-Atlantic Water Program requested a general framework to inform and guide the evaluation of the performance trading programs. This resulting report was developed by a workgroup comprised of ten individuals with extensive experience in the study, design, and evaluation of trading programs. While the impetus for this report was to improve evaluation of trading programs in the Chesapeake Bay region, the evaluation framework is broad enough to apply to trading programs in general

    Language history : A tale of two countries

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    This paper looks at the relationships between industry computer languages and those taught in universities. By considering the differences between two of the first countries to embrace programmable computers (USA and Australia) we find patterns that seem culturally independent. History shows a set of recurring problems for academics in choosing languages. This study shows that academics should be informed by history when making those decisions.2nd IFIP Conference on the History of Computing and EducationRed de Universidades con Carreras en Informática (RedUNCI

    Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

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    BACKGROUND: Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. RESULTS: Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. CONCLUSION: This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases

    Comparison of Quarterly and Yearly Calibration Data for Propensity Score Adjusted Web Survey Estimates

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    While web surveys have become increasingly popular as a method of data collection, there is concern that estimates obtained from web surveys may not reflect the target population of interest. Web survey estimates can be calibrated to existing national surveys using a propensity score adjustment, although requirements for the size and collection timeline of the reference data set have not been investigated. We evaluate health outcomes estimates from the National Center for Health Statistics’ Research and Development web survey. In our study, the 2016 National Health Interview Survey as well as its quarterly subsets are considered as reference datasets for the web data. It is demonstrated that the calibrated health estimates overall vary little when using the quarterly or yearly data, suggesting that there is flexibility in selecting the reference dataset. This finding has many practical implications for constructing reference data, including the reduced cost and burden of a smaller sample size and a more flexible timeline
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