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131.
Objectives. Despite the interest that social scientists have displayed in the rising rate of incarceration, little attention has been devoted to understanding its consequences for local areas. This is an important omission because prison construction has become a component of state and local economic development schemes. Indeed, there is a widespread belief that prison construction provides significant economic benefits to local areas. Methods. We analyze data on all existing and new prisons in the United States since 1960 and examine the impact of these prisons on the pace of growth (as measured by public, private, and total employment growth) in U.S. counties from 1969 to 1994. To our knowledge, our study is the first comprehensive and longitudinal assessment of the impact of prison construction on local areas. Results. We find no evidence that prison expansion has stimulated economic growth. In fact, we provide evidence that prison construction has impeded economic growth in rural counties that have been growing at a slow pace. Conclusion. Despite sharp ideological and intellectual differences, the critics and the advocates of the prison construction boom share the assumption that prisons can contribute to local growth, especially in hard‐pressed local areas. This belief flies in the face of mounting evidence that state and local initiatives rarely have a significant impact on growth; this belief is also contradicted by our analyses. 相似文献
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Kimberly M. Thompson Radboud J. Duintjer Tebbens Mark A. Pallansch Olen M. Kew Roland W. Sutter R. Bruce Aylward Margaret Watkins Howard Gary James P. Alexander Linda Venczel Denise Johnson Victor M. Cáceres Nalinee Sangrujee Hamid Jafari Stephen L. Cochi 《Risk analysis》2006,26(6):1571-1580
The success of the Global Polio Eradication Initiative promises to bring large benefits, including sustained improvements in quality of life (i.e., cases of paralytic disease and deaths avoided) and costs saved from cessation of vaccination. Obtaining and maintaining these benefits requires that policymakers manage the transition from the current massive use of oral poliovirus vaccine (OPV) to a world without OPV and free of the risks of potential future reintroductions of live polioviruses. This article describes the analytical journey that began in 2001 with a retrospective case study on polio risk management and led to development of dynamic integrated risk, economic, and decision analysis tools to inform global policies for managing the risks of polio. This analytical journey has provided several key insights and lessons learned that will be useful to future analysts involved in similar complex decision-making processes. 相似文献
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Assessing the Effect of Model Misspecifications on Parameter Estimates in Structural Equation Models
Model misspecifications may have a systematic effect on parameters, causing biases in their estimates. In the application of structural equation models, every interesting model is fallible. When simultaneously evaluating a model, it is of interest to study whether all parameters are affected by a misspecification. This paper provides three procedures for evaluating such an effect: (1) analyzing the path, (2) using a functional relationship, and (3) using a significance test. Analyzing the path is illustrated through a confirmatory factor model. This method is ad hoc but intuitive. A more rigorous approach is built upon the concept of orthogonality of two sets of parameters. When parameter a is orthogonal to parameter b, omitting parameter b will not affect the estimation of parameter a. The functional relationship of two sets of parameters is used to check their orthogonality. The distribution of the difference between estimates based on different models is obtained, which provides a Hausman–like way to check significant parameter differences that are due to biases. Examples illustrate that these procedures can provide valuable information on identifying parameter estimates that are systematically affected by a model misspecification. 相似文献
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Abstract Kassab (1990) makes an important methodological contribution by urging the use of robust regression methods in the study of community economic impacts and by indicating the utility of the bootstrap in assessing standard errors in robust regression. By introducing the notion of a contaminating distribution, we reconcile differences between her claim that ordinary least squares (OLS) regression is biased when outliers are present and standard linear model theory that does not make assumptions about the shape of the residual distribution in proving OLS an unbiased estimator. The contaminating distribution provides a framework for rural sociologists to link their statistical assumptions to a substantive understanding of the phenomena being studied. We suggest an alternative regression estimation strategy that may be more robust than the technique she uses. We also discuss an approach to bootstrapping that is more appropriate for macro-level social indicator data than the one she describes. An appendix discusses the software available for implementing these methods. 相似文献
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This paper examines race and gender differences in class consciousness and union support among a random sample of textile workers in a small North Carolina city. Class consciousness is treated as an ordinal variable consisting of class verbalization, class action orientation, and endorsement of egalitarian change. Union support denotes a recognition of the union's instrumental role in improving work and working conditions. The analysis reveals that blacks are significantly more class conscious and prounion than whites. On the other hand, males and females tend to share similar levels of class consciousness and union support. Comparisons by race, within gender and by gender, within race, are provided for finer distinctions and extended discussion. A multiple classification analysis reveals that racial differences persist and that gender differences remain unimportant when the covariates of age, job dissatisfaction, education, income, and skill are considered. 相似文献