Review Essay: What Is Left of the Left?

Sociological Forum -     

The Boston Area Diary Study and the Moral Citizenship of Care

This paper describes the theoretical foundations, empirical findings, and practical and philosophical implications of the Boston Area Diary Study (BADS), a study of the caring behavior of 44 participants over one calendar year. In particular, the paper presents an identification theory of care and discusses how it shaped the conceptualization, collection, and analysis of the data in a year-long diary study of daily voluntary assistance. The findings from the BADS (1) theoretically confirm the identification theory of care; (2) methodologically capture how individuals perceive and carry out caring behavior as a unity; and (3rpar; empirically document the existence of a moral citizenship in America that is substantially more vigorous than is implied by the usual indicators of civic and political citizenship.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

LEARNING ABOUT GRIEF FROM NORMAL FAMILIES: SIDS,STILLBIRTH, AND MISCARRIAGE*

Family therapists can learn a great deal that would be of utility to them in their clinical work from normal families grieving over the death of an infant. When a baby dies, families begin a long and difficult journey, a search for security and meaning in a world that for them has gone insane. The researcher discusses 10 probing, extremely difficult questions family members commonly pose in the aftermath of an infant death and offers guidelines that could be helpful to family therapists hoping to be of service to families in the process of healing and growing through this tragedy.     

AN ALGORITHM FOR THE CONSTRUCTION OF OPTIMAL OR NEAR-OPTIMAL CHANGE-OVER DESIGNS

This paper presents an algorithm for the construction of optimal or near optimal change-over designs for arbitrary numbers of treatments, periods and units. Previous research on optimality has been either theoretical or has resulted in limited tabulations of small optimal designs. The algorithm consists of a number of steps:first find an optimal direct treatment effects design, ignoring residual effects, and then optimise this class of designs with respect to residual effects. Poor designs are avoided by judicious application of the (M, S)-optimality criterion, and modifications of it, to appropriate matrices. The performance of the algorithm is illustrated by examples.     

The Independence of Aptitudes,Interests, and Career Beliefs

The importance of client beliefs in career counseling depends on their ability to add unique information about the client over and above that contributed by aptitudes and interests. The Career Beliefs Inventory was administered to 200 Australian students in grade 10 together with measures of Holland's RIASEC interest themes and scholastic aptitudes. The correlations between scales from the three domains showed clearly that beliefs made a contribution distinct from that provided by aptitudes and interests. Even though the results may reflect possible sampling or method variance, career beliefs in this sample added unique information to that traditionally used in career counseling.     

A theory of policy differentiation in single issue electoral politics

Voter preferences are characterized by a parameter s (say, income) distributed on a set S according to a probability measure F. There is a single issue (say, a tax rate) whose level, b, is to be politically decided. There are two parties, each of which is a perfect agent of some constituency of voters, voters with a given value of s. An equilibrium of the electoral game is a pair of policies, b ₁ and b ₂, proposed by the two parties, such that b _i maximizes the expected utility of the voters whom party i represents, given the policy proposed by the opposition. Under reasonable assumptions, the unique electoral equilibrium consists in both parties proposing the favorite policy of the median voter. What theory can explain why, historically, we observe electoral equilibria where the ‘right’ and ‘left’ parties propose different policies? Uncertainty concerning the distribution of voters is introduced. Let {F(t)} _{t ε T} be a class of probability measures on S; all voters and parties share a common prior that the distribution of t is described by a probability measure H on T. If H has finite support, there is in general no electoral equilibrium. However, if H is continuous, then electoral equilibrium generally exists, and in equilibrium the parties propose different policies. Convergence of equilibrium to median voter politics is proved as uncertainty about the distribution of voter traits becomes small.     

Grounded Neural Networking: Modeling Complex Quantitative Data

The latest advances in artificial intelligence software (neural networking) have finally made it possible for qualitative researchers to apply the grounded theory method to the study of complex quantitative databases in a manner consistent with the postpositivistic, neopragmatic assumptions of most symbolic interactionists. The strength of neural networking for the study of quantitative data is twofold: it blurs the boundaries between qualitative and quantitative analysis, and it allows grounded theorists to embrace the complexity of quantitative data. The specific technique most useful to grounded theory is the Self‐Organizing Map (SOM). To demonstrate the utility of the SOM we (1) provide a brief review of grounded theory, focusing on how it was originally intended as a comparative method applicable to both quantitative and qualitative data; (2) examine how the SOM is compatible with the traditional techniques of grounded theory; and (3) demonstrate how the SOM assists grounded theory by applying it to an example based on our research.