Prehistoric landscapes of the sonoran desert Hohokam

The Hohokam of southern Arizona are noted for greater duration of settlement than other major agricultural traditions in the archaeological record of the southwestern United States, including the Anasazi and Mogollon. The 40,000 square mile area inhabited by the Hohokam is marked by low elevation desert basins, but encompasses a range of topographic and climatic variability that shaped opportunities for prehistoric farming technologies. Irrigation from rivers was frequently associated with the longterm persistence of individual sites, while floodwater farming along ephemeral drainages was more often correlated with continuous occupation of hydrologically favored zones. Renewal of fields by waterborne nutrients and efficient practices in the use of natural resources countered the limited mobility options afforded by the Hohokam environment.In spite of a restrictive agricultural setting and an essentially static suite of productive technologies over many centuries, relationships among population, settlement, and landuse were redefined in evolving social and economic configurations. An example from the Tucson Basin illustrates differentiated patterns of settlement and agriculture arising in conjunction with increased levels of population and territorial integration in the late prehistoric period. Community organization among interrelated settlements incorporated a diversity of topographic zones and agricultural technologies in this high-risk context for prehistoric cultivators.     

Input-output evaluation of rural development: a forestry-centred application

The purpose of this paper is to analyse the role of forestry in the rural economy of Scotland. The Generation of Regional Input-Output Tables (GRIT) technique is applied to the estimation of input-output tables for rural Scotland. This is followed by a forestry-centred multiplier analysis. The results suggest that the forestry planting and harvesting sectors offer great potential for improving economic activity. However, their backward linkages with other rural industries seem to be limited. On the other hand, the backward linkages of wood-processing industries with the rest of the economy are strong. From this analysis, it is concluded that the joint development of forestry and wood-processing industries would promote economic development in rural Scotland.     

Mining the Data: Analyzing the Economic Implications of Mining for Nonmetropolitan Regions

Extractive industries such as logging and mining are generally expected to bring significant economic benefits to rural regions, but a growing number of findings have now challenged that common expectation. Still, it is not clear whether the findings of less–than–desirable economic outcomes are isolated or representative. In this article, we assemble literally all of the relevant quantitative findings on mining that we have been able to identify in published and/or technical literature from the United States. In the interest of rigor, we limit the assessment to cases in which strictly nonmetropolitan mining regions are compared against other nonmetropolitan regions and/or against those regions’ own experiences over time. Overall, 301 findings meet the criteria for inclusion. Contrary to the long–established assumptions, but consistent with more recent critiques, roughly half of all published findings indicate negative economic outcomes in mining communities, with the remaining findings being split roughly evenly between favorable and neutral/indeterminate ones. Positive findings are more likely to be associated with incomes than with poverty or (especially) unemployment rates, and they are more likely to come from the western United States, where much of the mining involves relatively large, new coal strip mines. Over half of all positive findings come from the years prior to 1982. In virtually all other categories, the plurality or majority of findings have been negative. When the patterns of findings are subjected to one–sample means tests, the only way to produce a significantly positive outcome is by combining all neutral/indeterminate findings with the positive ones, while focusing exclusively on incomes; by contrast, in the case of poverty or unemployment rates—as well as for the overall body of findings—the results are consistently and significantly negative, whether the neutral/indeterminate findings are combined with negative ones or omitted from the equations altogether. Until or unless future studies produce dramatically different findings, there appears to be no scientific basis for accepting the widespread, “obvious” assumption that mining will lead to economic improvement.     

Labor relations and technological change at Canadian Pacific Railway

There was a time in this fair land when the railroad did not run When the wild majestic mountains stood alone against the sun Long before the white man and long before the wheel When the green dark forest was too silent to be real For they looked into the future and what did they see They saw an iron road running from the sea to the sea Bringing the goods to a young growing land All up through the seaports and into their hands From “Canadian Railroad Trilogy” by Gordon Lightfoot The authors thank CPR managers and union officials representing CPR employees for their cooperation and patience in explaining the intricacies of the railroad industry. Special appreciation is extended to Jason Copping, Labour Relations Manager, for his facilitating our initial access to the company.     

The Texaco racial discrimination case and shareholder wealth

We analyze the wealth ejfects of the Texaco racial discrimination lawsuit both on the shareholders of Texaco and its major U.S. competitors. Employing a comprehensive data set which included every case docket entry and every Wall Street Journal article on the case as an experimental stimulus, our findings suggest that the overall cost of the case to Texaco shareholders exceeded $500 million, that Texaco's tribulations had little, if any, impact on the share prices of its major competitors, and that Wall Street Journal coverage of the case was highly correlated with significant changes in Texaco stock prices. This last finding provides significant support for Hite 's suppostion that newspaper editors “key ” on ex post stock price changes in selecting the events to be covered in the next day's edition. The authors are grateful to Kee Chung for helpful comments on earlier drafts and also acknowlege the help-ful assistance of the staff of the law library at the Cecil C. Humphreys School of Law at The University of Memphis.     

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.     

Sources of family violence

This paper suggests a direction for the exploration of the causes of family violence. Explanatory models of family violence were considered in this regard, with the recommendation that a multi-determined model should be considered to ensure the most accurate explanation. We suggest that family violence will be best understood and prevented or alleviated, if a model is used that considers the interaction of structural violence and the personality features of all the family members.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.