Bruce Wm. Pigozzi

Concepts in Social and Spatial Marginality

The purpose of this paper is to present a conceptual taxonomy of marginality resulting from two counterposed structural conditions within laissez‐faire on the one hand and controlled markets on the other. Marginality is a complex condition of disadvantage that individuals and communities may experience because of vulnerabilities which may arise from unequal or inequitable environmental, ethnic, cultural, social, political and economic factors. A typology of marginality is based on two primary and two derivative forms. The primary forms are contingent and systemic. The derivative forms are collateral and lever‐aged. Contingent marginality is a condition that results from competitive inequality in which individuals and communities are put at a disadvantage because of the dynamics of the free market whose uncertain and stochastic outcomes affect them adversely. Systemic marginality is a socioeconomic condition of disadvantage created by socially constructed inequitable non‐market forces of bias. Collateral marginality is a condition experienced by individuals or communities who are marginalized solely on the basis of their social and/or geographic proximity to individuals or communities that experience either contingent or systemic marginality. Lever‐aged marginality is a contingent or systemic disadvantage that people/communities are made to experience when their bargaining position in free markets is weakened by dominant stakeholders like transnational corporations which are able to leverage lucrative concessions by using the threat of alternative, often cheaper and marginalized (contingent or systemic) labour pools to which they can potentially take their business.

Tourist Carrying Capacity Measures: Crowding Syndrome in the Caribbean

Abstract International tourism is increasing at an unprecedented rate. Understanding the variety of national and local impacts of this increase is of importance to a growing number of governments. Butlers resort cycle model (1974, 1980,; 1991) provides for several long-term possibilities as to the relationship between crowding and growth. McElroy, de Albuquerque, and Dioguardi (1993) focus on one of those possibilities. Specifically, using their penetration ratio, they predict that as tourist crowding continues for a group of Caribbean islands, the appeal of these islands decreases in the eyes of potential tourists and that, as time increases, the growth rate of the affected islands, actually decreases. Our article indicates that such a simple, straight-line relationship between increased crowding and a decrease in the rate of change may not be inevitable; indeed, diseconomies of scale may be avoided. The use of a curvilinear regression function reveals how both positive and negative scale economies existed in the Caribbean during the years 1992 through 1996.

Population Pressure, Deforestation, and Land Degradation: A Case Study from the Dominican Republic

Population pressure, deforestation, and land degradation are major ecological concerns in developing countries. This research investigates causal linkages among interrelated physical and social processes in a case study conducted within the Plan Sierra resource management region of the Cordillera Central, Dominican Republic. Results of bivariate regression analysis, based on a sample of 450 traditional hillslope farms, support a linear relationship between population pressure and deforestation at two spatial scales. However, the strength of the relationship between population pressure and forest cover change decreases over a twenty-year time frame. Results also confirm a positive relationship between deforestation and land degradation. This case study contributes to an understanding of the precise nature of these relationships at sub-national scales of analysis.

A Hierarchy of Spatial Marginality Through Spatial Filtering

Abstract Taking a clue from classic time-series decomposition, this article demonstrates a spatial filtering and search technique that permits the partitioning of a measure of marginality, here measured as the percent of the population living at less than 50 percent of the poverty level, into macro, meso, and micro components. This approach supports theory that has argued for scale-specific explanations of spatial marginality. The technique also offers promise for many other types of investigations such as disease incidence, microclimate dynamics, and consumer preferences.

The Racial Gap in Childhood Blood Lead Levels Related to Socioeconomic Position of Residence in Metropolitan Detroit

Childhood lead poisoning in the United States remains a persistent, prevalent environmental public health problem, especially for children living in central-city neighborhoods. These neighborhoods typically are racially segregated, are in proximity to current and/or legacy lead emission sources, consist of older housing, and contain disproportionately African American or black children of low-income families. This research had two aims: (1) to determine whether average blood lead levels (BLLs) in children in the Detroit metropolitan area are related to the socioeconomic characteristics of the neighborhoods where they live and (2) to determine the estimated effect residential differences in the socioeconomic characteristics of neighborhoods have on average BLLs in non-Hispanic black and non-Hispanic white children. Data on pediatric BLLs were obtained from the Michigan Department of Community Health, and racial and socioeconomic data were obtained from the U.S. Census Bureau’s American Community Survey (2006–2010). The modified Darden-Kamel Composite Socioeconomic Index, multiple regression, and difference-of-means tests were used to determine the effect residential socioeconomic characteristics of neighborhoods have on average BLLs. Black segregated neighborhoods with lower socioeconomic characteristics were predictors of higher average BLLs in the children who lived there. When black and white children resided in neighborhoods of similar socioeconomic characteristics, the black-white gap in BLLs lessened. Significantly, after stratifying black and white children by age, living in the same neighborhoods of the lowest socioeconomic characteristics negated the black-white racial gap in BLLs entirely, but increasing levels of socioeconomic characteristics exacerbated the divide.

The Interaction of Economic Reforms, Socio-economic Structure and Agriculture in Mexico

National policydecisions in developing countries contribute to the increasing integration of agriculture into national and world economies. The spatial consequences of national policies, however, vary across regions and agricultural systems. Employing and adapting a methodology first proposed by King (1970), this study explores the relationship between national policy, agriculture, and population characteristics at the regional level in Mexico during the presidency of Carlos Salinas de Gortari (1988-94). Statistical analyses corroborate the hypothesis that the impact of policy reforms on the agricultural sector in Mexico is mediated by the characteristics of the population. Results suggest that government credit for agriculture and federal funding of rural development during the Salinas de Gortari administration were mediated by factors associatedwith the level of urbanization. The provision of commercial credit at the regional level, however, does not appear to depend on population characteristics. Disparities in the impact of national policies are attributed to a historical urban bias, the differential ability of more highly urbanized states to attract government funding, manage and implement programs, and the existence of highly profitable, commercial agriculture in more developed states. Copyright 2000 Gatton College of Business and Economics, University of Kentucky.

The relationship of neighborhood socioeconomic differences and racial residential segregation to childhood blood lead levels in Metropolitan Detroit

This study uses a new approach to assess the impact of different neighborhood characteristics on blood lead levels (BLLs) of black versus white children in metropolitan Detroit. Data were obtained from the Michigan Department of Community Health and the US Bureau of the Census American Community Survey. The Modified Darden-Kamel Composite Socioeconomic Index, bivariate regression, and the index of dissimilarity were used to compute neighborhood BLL unevenness by neighborhood characteristics. Neighborhoods with lower socioeconomic characteristics and high racial residential segregation predicted higher average childhood BLLs. This reveals a social spatial structure that will aid researchers/policymakers in better understanding disparities in childhood BLLs.

Estimation of input - output coefficients by means of employment data

A new procedure is presented for estimating input-output tables with limited survey data. Its significance lies in two areas: it demonstrates the efficacy of adjusting biproportionally the Leontief inverse rather than the matrix of technical coefficients and it shows the potential of utilizing independently gathered, less expensive, employment data in the column constraint. This procedure is tested by use of Washington input-output tables; the results compare favorably with conventional RAS adjustments.

Updating input - output tables using employment data: a reformulation

In this paper a method is developed for updating input — output tables using employment figures. The technique is an improvement over previous conventional adjustments because of the general availability and quality of employment data. Operating on the Leontief inverse matrix, this reformulation builds upon prior attempts to integrate employment data into the adjustment process. However, this model avoids the need to develop employment multipliers independently by using actual employment totals as the constraints. These constraints are derived in such a manner that row and column constraints each sum to the total regional employment.