Frederick L. Campbell

Developing and testing a decision aid for birth planning decisions

Abstract The article describes the development of a scheme to aid people in thinking through their decisions about whether to have a (another) child. First, a list of values (utilities) was gleaned from the literature, values (utilities) that children apparently fulfill for parents. Following this, seven married couples participated in the gradual modification of the list into a hierarchically structured set of values (utilities). Then two large groups of subjects were used to test the degree to which the hierarchy was meaningful to persons other than those who had participated in its development. Finally, as a feasibility study, two more couples (1) used the hierarchy to decompose their birth decisions into manageable chunks, (2) evaluated the chunks to indicate the relative utility of each chunk, and (3) assessed their subjective probabilities that those utilities represented in each chunk would be satisified if they were to decide to have the child. Computation of subjective expected utilities for having and for not having the child for each member of the couples permitted accurate postdiction of their birth decisions.

Subjective expected utility and the prediction of birth-planning decisions

This article is a companion to an earlier one which detailed the logic development and preliminary testing of a decision aid for birth planning. In brief the scheme consists of a hierarchical organized set of value categories related to having a child to which the decision maker assigns weights to indicate the relative utility of that category to him or her. Following that the decision maker assigns subjective probabilities to the categories to indicate how likely it is that these values would be fulfilled if a positive decision were made about having another child (or first child) in the next 2 years. The hierarchy breaks down into 3 main value-types: values centered on self and spouse (personal identity parenthood and well-being of family); values centered on childen (family characteristics health and well-being of children); and values centered on significant others (family friends and society). Married couples with variously sized families completed the birth-planning hierarchy outlined above. Predictions were made about a child-bearing decision in the next 2 years. Results showed that a subjective expected utility model predicted best (73% correct) for those couples who had not yet attained desired family size. Errors in prediction were not random and the reasons for false positives (couples predicting another child but not having one) are explored including the fact that the hierarchy does not capture the inherent ambivalence of couples; this concept of assenting on a questionnaire vs. real indecision on family continuation is discussed in terms of a decision threshold theory.

Family Building: A Social Psychological Study of Fertility Decisions

Decision theory, coupled with a hierarchically arranged questionnaire format, is discussed as a possible approach to the prediction of birth planning decisions. The empirical success of the scheme is examined in terms of interrelating attitudes, behavioral intention, desired family size, and birth planning behavior.

The Expectation-Threshold model of reproductive decision making

It is proposed that as expectations about parenting become increasingly high, couples have an increasing tendency to decide to have a(or another) child. Similarly, as parenting expectations become increasingly low, couples have an increasing tendency to decide on sterilization. Couples without extremely high or low expectations continue to use contraceptives. Expectations are defined as Subjective Expected Utilities (SEUs) for having or not having a child. Preliminary results support the model and suggest that the threshold for making these decisions is not at neutral, but is conservative so that couples must have fairly high or low expectations before making such binding decisions are parenting or sterilization. The fact that data reveal that this exists supports the Expectancy-Threshold model, but it also requires a change in SEU Theorys maximization rule for some kinds of decisions.

Size and the Administrative Component in Occupational Associations

The relationship between population size and organizational characteristics has long been of interest to sociologists (Simmel, 1902). If organization is conceptualized as a set of patterned relationships existing between functionally distinct units, then it may be properly considered as an attribute of a population. Characteristics of the population, such as size, therefore, should be related to various dimensions of organizational structure. Specifically, size is often identified as a causal factor in the rise of functional complexity and hence in the growth of the organizations administrative or coordinate component. This hypothesized relationship between organizational size and growth of the administrative component has received considerable attention over the last decade and a half (Anderson and Warkov, 1961; Bendix 1956: 221-223; Haas, Hall, and Johnson, 1963; Haire, 1959: 287-296; Hawley, Boland, and Boland, 1965; Lindenfeld, 1961; Melman, 1951; Raphael, 1967; Rushing, 1966; Terrien and Mills, 1955; Tsouderos, 1955). Unfortunately, the conflicting findings produced by this research have not provided a definite answer to the question under consideration. The purpose of this paper is to explore both the conceptual and methodological reasons for inconsistencies in previous tudies, and to present new data on this important problem. We will proceed by first considering some of the conceptual problems that have occurred in studies of growth and organizational change. Next, the relationship between organizational size and both the total and relative size of the administrative component will be examined using two different measurement procedures within a cross-sectional research design. Finally, the findings produced using these procedures will be compared with those gained from a longitudinal analysis of growth and change in the administrative component among a subset of our original population of organizations.