The “Helper” controversy in the construction industry

Helpers, whose role is to assist craftsmen, have been a subject of controversy in the construction industry for nearly a century. The AFL-CIO construction unions have attempted in various ways to control the work of helpers so that helpers cannot “pick up” the trade and then compete with craftsmen for jobs. With the help of the U.S. Department of Labor’s administration of the Davis-Bacon Act, these unions succeeded in almost eliminating the use of helpers on government-financed construction and most union jobs. This has meant that much unskilled and semiskilled work has been done by journeymen at skilled labor wages. The result has hurt union members and unionized contractors by aiding open-shop contractors, who use helpers extensively, to underbid their competitors and win increasing market share. This article examines the ramifications of the helper issue and related training problems from the turn of the century to the present, discusses various union policies, court decisions, and legislation affecting the issues, and concludes that the economies of utilizing helpers are sufficient to cast doubt on the efficacy or future success of current union attempts to limit narrowly the training and use of helpers. Professor Emeritus of Management; formerly, Director, Industrial Research Unit, and Chairman, Labor Relations Counsel.     

Book Reviews

The diagnostic tools examined in this article are applicable to regressions estimated with panel data or cross-sectional data drawn from a population with grouped structure. The diagnostic tools considered include (a) tests for the existence of group effects under both fixed and random effects models, (b) checks for outlying groups, and (c) specification tests for comparing the fixed and random effects models. A group-specific counterpart to the studentized residual is introduced. The methods are illustrated using a hedonic housing price regression.     

Predicting Insurance Losses Under Cross-Classification: A Comparison of Alternative Approaches

Various mathematical and statistical models for estimation of automobile insurance pricing are reviewed. The methods are compared on their predictive ability based on two sets of automobile insurance data for two different states collected over two different periods. The issue of model complexity versus data availability is resolved through a comparison of the accuracy of prediction. The models reviewed range from the use of simple cell means to various multiplicative-additive schemes to the empirical-Bayes approach. The empirical-Bayes approach, with prediction based on both model-based and individual cell estimates, seems to yield the best forecast.     

Interval Estimation for the Difference of Two Independent Variances

Analytical methods for interval estimation of differences between variances have not been described. A simple analytical method is given for interval estimation of the difference between variances of two independent samples. It is shown, using simulations, that confidence intervals generated with this method have close to nominal coverage even when sample sizes are small and unequal and observations are highly skewed and leptokurtic, provided the difference in variances is not very large. The method is also adapted for testing the hypothesis of no difference between variances. The test is robust but slightly less powerful than Bonett's test with small samples.     

Statistics for Quality and Productivity: A New Graduate-Level Statistics Course

The growing popular realization that American product quality and productivity are no longer without challenge for world leadership presents an opportunity for the American statistical community to make stronger contributions to sound industrial practice than it has in the past. Management consultants, such as Deming and Juran, are promoting philosophies that contain strong statistical components and are being heard by top U.S. executives. There are thus growing opportunities for industrial statisticians. Upon reviewing the content of typical graduate-level statistical quality control courses and books in the light of the present situation, we find them to be inadequate and in some cases to suffer from inappropriate emphases. In this article we discuss our perceptions of what is needed in the way of a new graduate-level course in statistics for quality and productivity (SQP). We further offer for discussion a syllabus for such a course (which is a modification of one used at Iowa State in the 1983 spring semester), some comments on how specific topics might be approached, and also a partially annotated list of references for material that we believe belongs in a modern SQP course.     

Covariate handling approaches in combination with dynamic borrowing for hybrid control studies

Borrowing data from external control has been an appealing strategy for evidence synthesis when conducting randomized controlled trials (RCTs). Often named hybrid control trials, they leverage existing control data from clinical trials or potentially real-world data (RWD), enable trial designs to allocate more patients to the novel intervention arm, and improve the efficiency or lower the cost of the primary RCT. Several methods have been established and developed to borrow external control data, among which the propensity score methods and Bayesian dynamic borrowing framework play essential roles. Noticing the unique strengths of propensity score methods and Bayesian hierarchical models, we utilize both methods in a complementary manner to analyze hybrid control studies. In this article, we review methods including covariate adjustments, propensity score matching and weighting in combination with dynamic borrowing and compare the performance of these methods through comprehensive simulations. Different degrees of covariate imbalance and confounding are examined. Our findings suggested that the conventional covariate adjustment in combination with the Bayesian commensurate prior model provides the highest power with good type I error control under the investigated settings. It has desired performance especially under scenarios of different degrees of confounding. To estimate efficacy signals in the exploratory setting, the covariate adjustment method in combination with the Bayesian commensurate prior is recommended.     

Muslim and Non‐Muslim Differences in Female Autonomy and Fertility: Evidence from Four Asian Countries

On the basis of research on paired Muslim and non‐Muslim communities selected in India, Malaysia, Thailand, and the Philippines, the authors test the hypothesis that greater observed Muslim pronatalism can be explained by less power or lower autonomy among Muslim women. Indeed, wives in the Muslim communities, compared to the non‐Muslim ones: 1) had more children, 2) were more likely to desire additional children, and 3) if they desired no more children, were less likely to be using contraception. However, the authors do not find that Muslim communities consistently score lower on dimensions of women's power/autonomy. Thus, aggregate‐level comparisons provide little evidence of a relationship between lower autonomy and higher fertility. Individual‐level multivariate analysis of married women in these paired settings similarly suggests that women's autonomy differentials do not account for the higher fertility, demand for more children, and less use of contraception among Muslim wives. These results suggest that explanations for Muslim/non‐Muslim fertility differences lie elsewhere.     

Husbands’ versus wives’ fertility goals and use of contraception: The influence of gender context in five Asian countries

Using data from Pakistan, India, Malaysia, Thailand, and the Philippines, we explore how gender context influences (1) husband-wife concordance in the demand for children and (2) the impact of each spouse's fertility preferences on contraceptive use. We also explore whether the husband's pronatalism can explain the wife's unmet need for contraception. The results suggest that gender context has little net effect on couples' concordance, but influences the relative weight of husbands' and wives' preferences in determining contraceptive use. Analysis of women's unmet need for contraception suggests that the husbands' pronatalism contributes to wives' unmet need, but only to a relatively small degree, especially in settings where unmet need is high. This is the case because the proportion of couples with differing fertility goals is small in most communities.     

Student homicidal violence in schools: an international problem

School homicides have been become a worldwide phenomenon. In the decade following the Columbine shooting there have been at least forty similar events in other countries. This article addresses the international scope of this problem and some of the complex conceptual issues that make student homicidal violence difficult to define and study. Meaningful research on risk and protective factors that can inform evidence-based preventive models is summarized.