Teaching Teachers to Teach Corporate Governance Differently

Journal of Management and Governance -     

Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

The twenty-percent majority: Pro-union bias in prevailing rate determinations

Each individual wage rate set by Davis-Bacon or by any similar state or local prevailing wage determination petrifies the outcome of competing views of how construction work should be staffed and paid on public works projects. Although presented with great precision (to tenths of a cent for both wages and fringe benefits), the level of wages themselves are of surprisingly little consequence: Those set at union levels soon rise, being automatically updated to new contracts and conditions; the rest fast become obsolete in any rising market, because surveys to update them are rare. But in addition to setting wage levels, determinations also delineate which jobs get to have rates set for them, and perhaps most critically, whether those delineated are identified as union or notunion. Whatever pattern is found may remain in effect for years or even decades, influencing which journeymen and laborers own what job tasks and who may perform what. Also, if a particular job happens to be set as union, it may bring with it dozens or even hundreds of related special job categories, grades of sub-groups, fine distinctions of fringe benefits, and complex divisions of geographic applicability based on local union jurisdictional areas. This study uses determinations recently made in Pennsylvania as an example to examine the mechanics of the wage-setting process. I find that, in addition to the endemic problems one might expect associated with a complex and partly judgmental process, every step of finding and setting prevailing rates includes overwhelming deference on the part of government towards union views and methods. It shows why unions representing less than 20 percent of the private construction work force consistently set the parameters controlling most of public construction. It ends with some suggestions on how better surveys and determinations could be made.     

ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

Opposition to Solid Waste Incineration: Pre- Implementation Anxieties Surrounding a New Environmental Controversy*

Despite sociopolitical controversy surrounding the solid waste crisis, little sociological attention has focused on this crucial environmental issue. Drawing on research from the technological controversies, environmental concern, and solid waste literatures, this study examines the pre-implementation anxieties of a Louisiana community faced with a proposal to build an incinerator in its backyard. Utilizing survey data, a causal path model is developed in which the perceived advantages of the technology, general environmental concern, and support for recycling initiatives are identified as explanatory variables of incinerator opposition. Implications of these findings for the study of technical controversies and the larger solid waste crisis also are suggested.     

Small Business Success Among Men- and Women-Owned Firms in Rural Areas1

Abstract Rural women have difficulty finding good jobs. Ownership of small businesses offers an alternative but the sales and income of women-owned firms are significantly lower than those of men-owned firms. Compared with men, women owners are more likely to operate smaller and newer businesses; however, these differences do not completely account for the gap in gross sales between men- and women-owned businesses. The strongest influences on business success are firm size, corporate status, and industrial sector. Though significant, the owner's gender is less important than these organizational characteristics. The factors influencing success of small businesses generally are the same for men- and women-owned businesses. More research on business networks and the start-up phase of small businesses is necessary for a better understanding of the sources of gender differences in success.