PROGRAM CHANGE, REVENUE EFFECTS, AND THE PATHOLOGY OF IMPROVED PERFORMANCE

In certain circumstances, improved performance in government programs can actually lead to declines in program impacts. Ironically, increases in efficiency do not invariably lead to increases in effectiveness. Regulatory programs are especially prone to this pathology of improved performance, as the targets of regulatory actions may increase avoidance tactics of program efficiency increases. Declines in effectiveness may not be discovered until revenues from the regulatory activities decline, because of weaknesses of internal monitoring systems in local government. Data on the licensing of businesses in Chicago are presented that illustrate the phenomena.     

Representation and Agenda Setting

We develop a new approach to the study of representation based on agenda setting and attention allocation. We ask the fundamental question: do the policy priorities of the public and of the government correspond across time? To assess the policy priorities of the mass public, we have coded the Most Important Problem data from Gallup polls across the postwar period into the policy content categories developed by the Policy Agendas Project ( Baumgartner & Jones, 2002 ). Congressional priorities were assessed by the proportion of total hearings in a given year focusing on those same policy categories, also from the Agendas Project. We then conducted similar analyses on public laws and most important laws, similarly coded. Finally we analyzed the spatial structure of public and congressional agendas using the Shepard‐Kruskal non‐metric multidimensional scaling algorithm. Findings may be summarized as follows: First, there is an impressive congruence between the priorities of the public and the priorities of Congress across time. Second, there is substantial evidence of congruence between the priorities of the public and lawmaking in the national government, but the correspondence is attenuated in comparison to agendas. Third, although the priorities of the public and Congress are structurally similar, the location of issues within the structure differs between Congress and the general public. The public “lumps” its evaluation of the nations most important problems into a small number of categories. Congress “splits” issues out, handling multiple issues simultaneously. Finally, the public tends to focus on a very constrained set of issues, but Congress juggles many more issues. The article has strong implications for the study of positional representation as well, because for traditional representation to occur, there must be correspondence between the issue‐priorities of the public and the government. We find substantial evidence for such attention congruence here.     

Three‐Dimensional Neurointerpolation of Annual Mean Precipitation and Temperature Surfaces for China

Climatic variables such as annual mean precipitation and temperature display complex and nonlinear variation with latitude, longitude, and elevation. Neural networks are universal approximators and very good at detecting and representing nonlinear relationships between dependent and independent variables. In this paper we use resilient backpropagation (Rprop) neural networks to interpolate annual mean precipitation and temperature surfaces for China. Climate surfaces are interpolated from a total of 288 long‐term climate station data points using latitude, longitude, and elevation derived from a 5‐kilometer resolution digital elevation model. Initial trials of Rprop suggested very fast learning, insensitivity to selection of learning parameters, and a tendency not to overtrain. Cross‐validation was used to determine the best network structure and assess the error inherent in climate interpolation. With the error explicit, the final neurointerpolations of annual mean precipitation and temperature were constructed using all 288 climate station data points. Maps of residuals are also presented. The neurointerpolation of temperature was very successful and captures most of the regional trends found in established climate maps of China as well as significant topographically defined detail. For annual mean temperature the Rprop neural network was found to be an accurate and robust global spatial interpolator. However, the precipitation surface captures only the major latitudinally and continentally defined trends and misses many subregional rainfall features probably because of the influence of other nonparameterized atmospheric and topographic factors.     

Reconceptualizing the Policy Subsystem: Integration with Complexity Theory and Social Network Analysis

The concept of the policy subsystem is an essential building block for several of the basic frameworks of policy process studies. Over time issues have become more complex, crossing subsystem boundaries, and so subsystems have escalated in their complexity as well. It is increasingly insufficient to study just one policy subsystem and so scholars have turned to studying boundary‐spanning regimes or policy networks. In this essay, we review the major contributions to developing the concept of a policy subsystem and trace its evolution into broader conceptualizations like issue and policy networks. We argue that the future for theories of the policy process is in more explicit integration of complexity theory and more effective modeling of subsystems with the utilization of social network analysis. In closing, we discuss the enduring nature of the concept of policy subsystems and highlight studies that continue using it in innovative ways.     

Modeling agricultural potential in Chaco Canyon during the Bonito phase: a predictive geospatial approach

This study presents a geospatial analysis of surficial hydrology and geomorphology and their relationship to potential agricultural productivity in order to better understand the economic role of water in Chaco Canyon during the Bonito Phase (ca. AD 850–1150). Defined as the Natural Agricultural Suitability Analysis, the foundation of this study is a hierarchical geospatial analysis that integrates six key natural factors: slope, soil texture, soil depth, non-catastrophic overbank flooding potential, drainage flow length, and drainage proximity and flow potential. These factors are combined through a raster weighted overlay function to generate composite suitability map that offers a testable proxy for variability in relative agricultural potential during the Bonito Phase at Chaco. The rationale for including this set of natural factors is based largely on ethnographic and modern agricultural studies, but the predictive model differs from previous studies of agricultural potential in that it is independent of the specific archaeological distribution of evidence of agriculture in the study area. The results of this analysis suggest that previous models of Chacoan agricultural productivity have underestimated local production capacity. Previous studies have focused solely on floodplain contexts, whereas this study points to a more comprehensive and geographically distributed use of the landscape.     

Proto-Urban Establishments in Inner Asia: Surveys of an Iron Age Walled Site in Eastern Mongolia

Walled sites attributed to the Xiongnu steppe empire (2nd century b.c.–1st century a.d.) constitute the earliest investments in explicitly non-mortuary built environments among pastoralists of the Mongolian Steppe. These permanent constructions are important precedents to the medieval towns of subsequent steppe empires, yet very little of the complete layouts and surrounding remains of the large enclosures are understood. Our investigations of the walled site at Kherlen-Bars in eastern Mongolia are among the first surveys to fully document all aspects above and below ground across an entire Iron Age walled site area. In addition to detailed documentation of the large structures, our geomagnetic prospections and digital elevation modeling brought to light numerous small sub-surface and subtle-surface features that show such early walled sites, often deemed virtually empty, to be far more complex and diachronic in their formation processes and possible functions.     

Stone Age midden deposition assessed by bivalve sclerochronology and radiocarbon wiggle-matching of Arctica islandica shell increments

Sclerochronology, the study of the skeletal diaries of mollusks and corals, is a high-resolution geochronological tool of versatile usage in archaeology and paleontology with increasingly growing opportunities. Much of the recent efforts have concentrated on building multi-centennial bivalve growth records using annually deposited increments in the Holocene shells, comparable to tree-ring chronologies. In the context of geoarchaeology, the hitherto unachieved potential includes the application of sclerochronology to reconstruct long-term settlement histories. Here we contribute to both of these critical issues by presenting the first multi-shell sclerochronology constrained by methods originally developed in tree-ring research, using anthropogenically deposited bivalve shells of Arctica islandica excavated from a Stone Age midden in North Norway. Our systematic chronological approach to shell growth histories lays the foundation for a multi-dimensional dating framework that interacts between the incremental, radioisotopic and stratigraphic evidence. We show how the crossdating within and between the single-shell records yields a 155-year multi-shell sclerochronology, supported by the ¹⁴C AMS dates, that demonstrates minimum midden accumulation of 82 years and a depositional rate of 0.3 cm/yr. Sclerochronology paves the way for radiocarbon wiggle-matching, which narrows the probabilistic 2-σ uncertainty range for the oldest and youngest ¹⁴C AMS dates to 3150–2980 and 3060–2890 BC, respectively. We attribute the spectral characteristics of the chronology primarily to the North Atlantic Oscillation, suggesting essentially similar influences of climate variability on the Stone Age culture and our own society.