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The article presents a case study in the diffusion of social "Scientific" research. The authors aims at a refinement and extension of researcher Michel Foucault's argument. His concern is not, however, with academic philosophy. Rather, he seeks to understand how statistically based academic studies in economics and sociology become part of politically charged social policy discussions and popular culture in the United States. The critique borrows and elaborates Foucault's information-processing metaphor and further develops his argument using the details of a recent example of distorted transmission. The author also offer explanations for such distortion and suggestions for its remedy. The academic survival of quantitative social researchers depends on their discovering social cause and effect relationships. Project directors in research organizations dependent on government funds must discover such relationships or risk decreasing the flow of such funds. Reporters will find a story in the discovery, not the absence, of such relationship. But relatively few discoveries of a social cause and effect relationship withstand a complete sensitivity analysis. So practices that slight such analyses become taken for granted. If a sensitivity analysis is done, it may not be very complete witness the attrition sensitivity analysis done by the researchers that neglects self-selection and subject-reporting.

The article discusses that three classical philosophical problems and four problems in social-level analysis play a role in imposing limits on the use of statistics in social-level empirical research and in planning. Although statistical method is very popular in social-level analysis, empirical evidence of (relatively) unequivocal success on this level occurs less frequently than in either physics or biological-level analysis. The limits for statistics in social-level analysis can be overcome while remaining within the statistical way-of-knowing, but only partially. Subjective or personal probability overcomes the difficulties of objective probability but subjective probability is in turn limited, if arbitrariness is to be avoided, to a code of consistency for the person applying it. Statistically sophisticated causal-modeling approaches can partially (but only incompletely) test for causality experimentally. Assumptions about the underlying distribution can sometimes be weakened but often not without creating nearly insurmountable calculative difficulties.

The article presents abstracts of various articles published in the periodical "Quality and Quantity." The essay "The Limits of Statistics in Planning Analysis," by Leland Gerson Neuberg, consists of five parts, It is argued that distinguishing various levels--e.g. physical, biological, psychological, and social--of the world helps on to understand why such apparently resolved philosophical questions as free will determinism recur. In the article "Symmetric Representation of Political Trends in Three-Party Systems With Some Properties, Extensions and Examples," by William L. Miller focuses on election outcomes in a three-party system. This paper attempts to list some of the useful properties of these elegantly simple diagrams and to provide a range of examples sufficient to show that they are more than a mathematically elegant toy. In "Pure Mobility and Pure Exchange Mobility," by Gunnar Persson, there seems to be an agreement among social scientists analyzing mobility that there are two types of social mobility. The so-called exchange mobility (sometimes also denoted pure mobility) is not explicitly defined but appears as a residual, i.e. as the toal mobility less the structural mobility.