AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.     

Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

Structure and process in occupational mobility

The distinction between structure and process in occupational mobility has been a dominant theme in contemporary research. While successive attempts to “solve” the structure/process dilemma have typically focused on new methodological procedures, we emphasize the conceptual issues underlying the distinction as a basis for further analysis. We introduce a simple two-stage model for the specification of mobility structure and process and use this model to evaluate current methodological “solutions” to the analysis of mobility.     

Assessing the devolution revolution: How accurate are state-level estimates from the current population survey

The devolution of many social policy responsibilities from the Federal government to states has prompted increased interest in state-level measures of need. One data source that could be used to provide more state-level information on a variety of topics is the Current Population Survey (CPS). During the past ten years the CPS has been used to produce state-level estimates on a variety of measures. However, there has been little systematic evaluation of these data. This paper provides measures of accuracy for several state-level estimates derived from the CPS. These include standard errors for single-year estimates, three-year averages, and five-year averages of the March CPS measures; standard errors for three-year averages of 12-month CPS files; and comparison of CPS-based estimates to data from the Decennial Census. The paper also examines the relative accuracy of CPS estimates based on states' size. The information in this study will help analysts better understand the tradeoffs between timeliness and accuracy to be considered when using state-level estimates derived from the CPS.     

Reexamining the moving to opportunity study and its contribution to changing the distribution of poverty and ethnic concentration

For the past decade and a half a concerted effort has been undertaken to determine whether policy interventions in residential location can solve the problems of inner-city poverty and racial concentration. Studies based on data from the Gautreaux litigation and the U.S. Department of Housing and Urban Development (HUD)-sponsored Moving to Opportunity (MTO) program have provided an overall optimistic interpretation of the possibilities of improving inner-city lives via mobility vouchers and counseling. A reanalysis of the data from the MTO program, focusing specifically on African American households, suggests greater caution in the interpretation of the findings from either Gautreaux or the MTO program. No statistically significant difference exists between the percentage of poor or the percentage of African Americans in the current neighborhoods between MTO and Section 8 experimental groups. In some cases, there is no statistically significant difference between those who move with a voucher and those who move without any assistance at all. Although there is some evidence that MTO programs have brought specific gains for individual families, claims for the MTO program as a whole need to be treated with a great deal more caution than they have been to date.     

MANAGING ACADEMIC INTERDISCIPLINARY RESEARCH PROJECTS*

This field study provides variables that can be used by practitioners as action levers and by future researchers as the basis for theoretical development. Conclusions from relevant literature and findings from interviews with interdisciplinary research management identified forty variables that were viewed as important to interdisciplinary research project success. After adjusting the data for reliability attenuation, these variables were further analyzed to identify the best prediction equation. The findings suggested that project age or the longevity of the project and open discussion of disagreements were the best predictors of performance.     

THE EFFECT OF MASCULINE AND FEMININE BRAND NAMES ON THE PERCEIVED TASTE OF A CIGARETTE *

The purpose of the current study was to determine whether brand name can affect the public's evaluation of a product. All subjects smoked identical cigarettes. One group of subjects, however, knew the cigarettes by the name of “Frontiersman,” a masculine name, while the other group knew the cigarettes as “April,” a feminine name. Male and female subjects were asked to rate the cigarette on seven measures. Results show that women gave a more positive evaluation to the cigarette purportedly named “April,” while men gave a more positive evaluation to the identical cigarette when they thought it was named “Frontiersman.” In addition, women reacted more strongly than did men to brand name influence.     

SOME TESTS OF BINOMIAL PROBABILITY ASSESSMENTS

A replication of the Alpert-Raiffa probability assessment experiment is used to motivate the development of several tests for evaluating assessors. The tests permit an evaluation of an assessor's accuracy in estimating target quantities and in estimating his own uncertainty as well. Assumption of normal subjective distributions permits the determination of subjective variances. Data from trial assessments are employed to test models which assert that assessed quantities are equal to subjectively assessed error variances. Several tests of the latter type are compared using data from individual, as well as pooled, assessors.     

SENSITIVITY ANALYSIS WITH INTERACTION EFFECTS

The purpose of this paper is to extend the sensitivity analysis methodology as it applies to linear programming. The methodology developed herein is concerned with those changes in a technological coefficient that cause simultaneous changes in the relevant cost coefficients of the objective function. By proceeding from the definitions of feasibility and optimality, the authors develop formulas for determining bounds on the extent to which a technological coefficient, which has a predetermined effect on the corresponding cost coefficient, can vary without changing the optimal set of activities. After the formulas are developed, their use is demonstrated on a product-mix problem. This technique is of interest because changes in the rate at which an input is utilized can be expected to change the cost per unit of a resulting product. This interdependence should be recognized whenever a sensitivity analysis is performed on a technological coefficient of either a cost minimization or a contribution margin maximization problem.