Spatial Patterns of Crime in Israel: Investigating the Effects of Inter-urban Inequality and Proximity

Many crimes in Israel, specifically property-related, are perpetrated by those who live outside localities where the crime is committed. As a result, crime rates are strongly affected by settlement patterns: Affluent localities surrounded by poor towns tend to exhibit relatively high crime rates. In order to measure the effect of urban inequality and proximity on crime rates, the Index of Relative Income (IRI) is proposed. This index is estimated as the ratio between the average income in a town and that in its neighbouring localities. As multivariate analysis indicates, the proposed index helps to explain the variation of property crime rates across urban localities, implying that the spatial unevenness of urban development (i.e. aerial proximity of affluent and poor towns) may spur property crimes. The findings of the present study lend support to regional development programs, aimed at minimizing spatial disparities in regional and urban development.

Measuring Regional Disparities in Small Countries

Though individual studies of regional disparity may deal with separate development measures - population growth, wages, welfare, regional productivity, etc. - the use of an integrated indicator is often essential, particularly if a comparative (cross-country) analysis is required. In order to measure the extent of disparities, various indices of inequality are commonly used. The goal of present study was to determine whether commonly used inequality measures (Gini, coefficient of variation, etc.) produce meaningful estimates when applied to small countries, thus making it possible to compare the results of analysis obtained for such countries with those obtained elsewhere. As we argue, a small country may differ from a country of larger size in three fundamental features. First, it is likely to have a relatively small number of regional divisions. Second, its regional divisions are likely to vary considerably in their population sizes. Lastly, regions of a small country may rapidly change their rank-order positions in the country-wide hierarchy, by changing their attributes (e.g., population and incomes). In contrast, in a large country such rank-order changes may be both less pronounced and slower-acting. In order to formalize these distinctions, we designed simple empirical tests, in which income and population distributions, presumably characteristic for small countries, were compared with a “reference” distribution, assumed to represent more accurately a country of a larger size. In the latter (reference) distribution, the population was distributed evenly across regional divisions and assumed to be static. In the first test, we checked whether the overall number of regions matters. In the second, we tested whether different inequality indices respond to differences in the regional distribution of population, viz., evenly spread population in the reference distribution vs. unevenly spread population in the test distribution. Finally, in the third test, we verified whether different inequality indices were sensitive to the sequence in which regions are introduced into the calculation. Somewhat surprisingly, none of the indices we tested appeared to pass all the tests, meaning that they may produce (at least in theory) misleading estimates if used for small countries. However, two population weighted indices – Williamson and Gini - appeared to exhibit only minor flaws and may thus be considered as more or less reliable regional inequality measures. Although further studies on the performance of different inequality indices may be needed to verify the generality of our observations, the present analysis clearly cautions against indiscriminate use of inequality indices for regional analysis and comparison.

Spatial Patterns of Urban Growth - Does Location Matter? a Case Study of Nepal

Between 1952 and 2001, the number of urban settlements in Nepal grew from 10 to 58, while their share in the country’s population increased from 2.6 to 14.4%. However, the spatial distribution of urban growth was uneven. The fastest growing urban localities are situated near major population centers, close to highways, and in the vicinity of the In-dian border. Urban localities elsewhere exhibited sluggish economic growth and poor socio-demographic performance. Data for this analysis were drawn from databases maintained by Nepal’s Central Bureau of Statistics; the Municipalities’ Association; the Ministry of Local Development and its Department of Topographical Survey. In the GIS-assisted analysis, spatial reference data (e.g., distances between individual municipalities and major rivers, roads, international borders and major population centers) were matched against five performance indexes, viz. annual population growth, per capita in-come and expenditures of local municipalities, telephone ownership, number of primary schools, and number of industries.

On Ecological Fallacy and Assessment Errors Stemming From Misguided Variable Selection: Investigating the Effect of Data Aggregation on the Outcome of Epidemiological Study

In behavioral studies, ecological fallacy is a wrong assumption about an individual based on aggregate data for a group. In the present study, the validity of this assumption was tested using both individual estimates of exposure to air pollution and aggregate air pollution data estimated for 1,492 schoolchildren living in the in vicinity of a major coal-fired power station in the Hadera sub-district of Israel. In 1996 and 1999, the children underwent subsequent pulmonary function (PF) tests, and their parents completed a detailed questionnaire on their health status, and housing conditions. The association between children’s PF development and their long-term exposure to air pollution was then investigated in two phases. During the first phase, the average rates of PF change observed in small statistical areas in which the children reside were compared with average levels of air pollution detected in these areas. During the second phase of the analysis, an individual pollution estimate was calculated for each child covered by the survey, using a "spatial join" tool in ArcGIS. While the analysis of aggregate data showed no significant differences in the PF development among the schoolchildren surveyed, the comparison of individual pollution estimates with the results of PF tests detected a significant negative association between changes in PF results and the estimated level of air pollution. As argued, these differences are attributed to the fact that average exposure levels are likely to cause a misclassification bias of individual exposure, as further demonstrated in the study using pattern detection techniques of spatial analysis (local Moran's I and Gettis-Ord statistic). The implications of the results of the analysis for geographical and epidemiological studies are discussed, and recommendations for public health policy are formulated.

Interregional inequalities in Israel: Explanatory model and empirical data

An explanatory model of regional inequality is proposed, which attempts to explain a spatial distribution of different income groups. According to this model, such a distribution is a function of the relation between the cost of living in a particular geographic area and actual income of its inhabitants. The applicability of this model to spatial inequalities in Israel is investigated, using data from five subsequent censuses of population and housing. The analysis indicates that there is no universal trend in the development of inequalities, examined from either a temporal or a spatial point of view. Instead, the extent of interregional disparities appears to differ when various indicators of inequality are considered. Measures of population distribution and wealth indicate the highest extent of interregional disparities, whilst the country's regional development appears to be the least uneven when indicators of education and participation in the labor force are considered. Temporally, most indicators of welfare and population distribution tend to diverge over time, reflecting increasing interregional disparities. In contrast, variables related to education and housing tend to converge, indicating a reduction in inequality. Moreover, the change in inequality appears to differ across various geographic areas: Whereas development in the central part of Israel has tended to become more uniform over time, the country's peripheral regions have developed towards further polarization of their socio-economic development. As a result of the analysis, several strategies are proposed aimed at reducing the extent of interregional disparities.

Komarovita

Los anlálisis dieron Si02 23,50, TiO2 2,50, Nb2 05 47,00, A1208 1,00, Fe208 1,50, MnO 5,00, CaO 4.70, Na2O 0,85, K2O 0,30, H2O 12,00, F 1,21, total 99,56 - (O = F2) 0,51 = 99,05 %.(...

On the possibility of the reaction (CuMoO4 + C), using the apparent activation energy method

This article discusses the calculation of the apparent activation energy (CuМоO4 + C) on the DTA (Differential Thermal Analysis) curve, to study and optimize the time-temperature synthesis mode, in particular, the activation energy. Activation energy allows us to investigate the elementary act of chemical interaction. Thus, we propose to use this method to calculate the interaction of Eact (CuМоO4 + C) in the solid phase of hardening occurring during synthesis. These results allow us to trace how much energy is expended to start the reaction

On the possibility of the reaction (CuMoO4 + C), using the apparent activation energy method

This article discusses the calculation of the apparent activation energy (CuМоO4 + C) on the DTA (Differential Thermal Analysis) curve, to study and optimize the time-temperature synthesis mode, in particular, the activation energy. Activation energy allows us to investigate the elementary act of chemical interaction. Thus, we propose to use this method to calculate the interaction of Eact (CuМоO4 + C) in the solid phase of hardening occurring during synthesis. These results allow us to trace how much energy is expended to start the reaction