Matt Grossmann



?The Variable Politics of the Policy Process: Issue Area Differences and Comparative NetworksMatt GrossmannAssistant Professor of Political Science, Michigan State University303 S. Kedzie HallEast Lansing, MI 48823(517) 355-7655matt@AbstractThe politics of policy issue areas differ in multiple ways, including the venues where policies are enacted, the frequency and type of policy development, the relative importance of different circumstantial factors in policy change, the composition of participants in policymaking, and the structure of issue networks. The differences cannot be summarized by typologies because each issue area differs substantially from the norm on only a few distinct characteristics. To understand these commonalities and differences, I aggregate information from 231 books and 37 articles that review the history of American domestic policy in 14 issue areas from 1945-2004. The histories collectively uncover 790 notable policy enactments and credit 1,306 actors for their role in policy development. The politics of each issue area stand out in a few important but unrelated aspects.Scholars seek to understand how the political system produces public policy, but the answers may differ across issue areas. Though cognizant of these likely differences, scholars rarely consider them systematically. Across issue areas, does American national policymaking take place in the same venues with the same frequency? Is the relative importance of different political circumstances similar? Are the composition of participants in policymaking and the structure of the networks that connect them similar? If differences are widespread, can they be easily summarized by a typology? This paper reviews American federal policymaking in 14 broad domestic issue areas since World War II: agriculture, civil rights & liberties, criminal justice, education, energy, the environment, finance & commerce, health, housing & development, labor & immigration, macroeconomics, science & technology, social welfare, and transportation. Across these issue areas, neither the causal factors in the policy process nor the composition and structure of issue networks are universal. Each issue area is distinct from the others on a few characteristics, but typical in most respects. Separable types of policymaking do not follow from issue area categorizations. As a result, investigations of policymaking are likely to focus on particular aspects of the policy process based on issue area case selection decisions, even though they seek generalized knowledge. The relevant circumstances and actors change with the issue territory, as do the relationships among actors and the relevant political circumstances. Rather than assuming universality in the policy process, relying on typologies, or creating unique theories for each issue area, scholars should be attentive to the few ways that each issue area differs from the others. I address these variations using historical studies of policymaking. First, I compare general theories of the policy process, policy typologies, and studies of issue networks. Second, I argue that issue area differences are best conceptualized as issue-specific exceptions to general patterns, rather than categorical distinctions based on underlying dimensions. Third, I explain the method, which relies on a content analysis of 231 books and 37 articles that review policy history. Fourth, I review the record of significant policy enactments in each issue area and the explanations for policy change found in these sources. Fifth, I analyze the networks associated with each policy area, relying on information about the actors credited with policy enactments by historians. Sixth, I search for underlying dimensions of issue area differences as well as clusters of issue types. Finally, I provide descriptions of the unique features of each issue area to guide future scholarship. Issue Area Politics and the Policy ProcessMany theories of the policy process largely sidestep the question of differences across issue areas and are meant to apply to many domains. Punctuated-equilibrium (PE) accounts (Baumgartner and Jones 1993) argue that significant policy change is unlikely without a large increase in consideration of a problem. The multiple streams (MS) account emphasizes the multiple, largely independent, streams of problem definition, politics, and policy (Kingdon 2003). The advocacy coalition framework (ACF) focuses on the ideas and beliefs developed by interest group and government proponents of policy change (Sabatier and Jenkins-Smith 1993). Although these theories are all applied flexibly to different issues, their applications tend to concentrate in particular areas. Studies using PE focus more on budgets (Jones and Baumgartner 2012), the MS account draws more from transportation and health (Zahariadis 2007), and nearly 64% of applications of the ACF focus on environmental or energy policy (Weible, Sabatier, and McQueen 2009). Issue area differences could help reconcile accounts of policymaking from different theoretical perspectives. For example, PE accounts imply that significant policy change is driven by episodic agendas; other incremental policy changes are thought to be less important. In contrast, historical approaches to policy change (Pierson 2004) argue that most significant policymaking is developmental; it relies on a path dependent process where early decisions constrain later decisions. Alternatively, some issue areas may be more episodic and others more path dependent. Some theories of the policy process explicitly analyze issue area differences. They tend to involve issue categorization schemes that focus on one or two dimensions of variation associated with clear types. Theodore Lowi (1964) proposes a three-part typology: redistributive, distributive, and regulatory. The idea is that scholars should expect to find differences in the politics of each issue area based on the kind of policy under debate and who has something to gain or lose from policy action. Similarly, James Q. Wilson (1980) argues that policy issues can be divided into types based on whether the costs and benefits of policy action in the area are concentrated or dispersed: interest group politics where both are narrow, entrepreneurial politics where only costs are concentrated, client politics where only benefits are concentrated, and majoritarian politics where both are broad. These typologies have been difficult for scholars to follow, since most policy areas have elements of multiple types. They have not proved especially fruitful in understanding policy area differences, but new typologies have nonetheless proliferated (Smith 2002). The continued interest in typologies highlights the need to understand variation across issue areas in the venues where policymaking takes place and the factors responsible for policy change. I investigate this variation, focusing on several categories of explanations for policy referenced in both issue area histories and the general literature on public policy: media coverage, public opinion, interest groups, international factors, state and local factors, research, events, and path dependence.If differences across issue areas produce distinct politics, scholars should also observe different kinds of networks emerging in different areas. In the classic formulation of “issue networks,” Hugh Heclo (1978) argues that experts form relationships based on reputations for issue-specific knowledge. Other scholars analyze these relationships, finding a “hollow core” with no central player arbitrating conflict in many issue domains (Heinz et al. 1993). Yet comparative analysis of issue networks is rare. In addition, some scholars argue that not all policy communities are large and broad enough to merit the label of issue networks (Marsh and Rhodes 2004). Others argue that policymaking in some areas may instead resemble iron triangles involving a set of client interest groups, an executive agency, and relevant congressional committees (Berry 1989). To investigate variation across networks, I examine the composition of actors involved in each issue area and the configuration of their relationships.Issue Area Differences as Exceptions to General PatternsExtant research has not uncovered typologies that successfully explain how either the politics of policymaking or the character of networks differ across issue areas. Kevin Smith (2002, 381) advocates a move from typologies to taxonomies, classifying items “on the basis of empirically observable and measurable characteristics.” This paper generally takes this approach, addressing two fundamental problems of policy typologies. First, typologies assume that differences in the politics of issue areas can be distilled into only a few important dimensions. Second, they assume that most issue areas will fall in a clear zone along these dimensions, enabling scholars to place them in boxes. Both assumptions may be false. Issue areas may have broadly similar policy processes and each issue area may stand out in only a few important aspects. This perspective should apply to both the institutions and circumstances that make policy change possible (the focus of the policy process literature) and the actors responsible for policy change and their relationships (the focus of the issue networks literature). Whether scholars are looking at where and how often policy change occurs, the role of circumstantial factors in driving policy development, or the people and organizations that jointly bring it about, they should not expect issue area differences to conform to any typology. Issue area differences manifest themselves in both obvious and subtle ways. It should be no surprise that criminal justice policy change happens more often in the courts compared to other areas; after all, a large proportion of court proceedings confront related issues. Learning that energy policy is less likely to be affected by public opinion than other areas, in contrast, may elicit more surprise. These differences are unlikely to be reducible to a few categories. Categorizing criminal justice as a court-centered issue area, for example, would miss all of the ways that it is similar to other issue areas while highlighting only one of its features. Similarly, categorizing energy policy as immune from public opinion would also put too much emphasis on a single aspect of its politics.Issue network differences are also unlikely to allow categorization into separable types. In particular, the composition of networks (such as the partisan or institutional affiliations of its members) may vary independently of their structure. I find that a large issue network bridging two branches of government determines macroeconomic policy, for example, but this may not correspond to a category that any other issue network fits well within. Issue area differences are thus unlikely to correspond to the characteristics that make typologies useful. Scholars should instead specify the differences between issue areas, even if they only amount to a series of exceptions to the typical policy process and the common features of issue piling Policy Area HistoriesSpecifying the differences across issue areas requires comparative studies of many different policy processes. To make that possible, I rely on secondary sources of policy history. Policy specialists often review extensive case evidence on the political process, attempting to explain how, when, and why public policy changes. These authors, who I call policy historians, identify important policy enactments in all branches of government and produce in-depth narrative accounts of policy development. David Mayhew (2005, 245-252) used policy histories to produce his list of landmark laws; he found them more conscious of the effects of public policy and less swept up by hype from political leaders than contemporary scholarly or journalistic judgments. The analysis here relies on 268 books and articles that review policy history since 1945. I compile published accounts of federal policy change in 14 issue areas, each corresponding to a category from the Policy Agendas Project (PAP). I exclude the foreign policy areas of defense, trade, and foreign affairs, but cover nearly the entire spectrum of domestic policy areas. For each issue area, I search multiple book catalogs and article databases using keywords from the topic lists and subcategories available at . To find additional sources, I use bibliographies and literature reviews. Rather than sample, I construct a population of sources based on several exclusion criteria. To focus on broad historical reviews of the policy process, I exclude sources that do not identify the most important enactments, those that focus on advocating policies or explaining the content of current policy, and those that cover fewer than ten years of policymaking. I also exclude sources that analyze the politics of the policy process from a single theoretical orientation without a broad narrative review of policy history. The full list of sources, categorized by issue area, is available in the supporting materials on the journal’s website. With the help of research assistants, I read each text and identified significant policy enactments. I include policy enactments when any author indicated that the change was important and attempted to explain how or why it occurred. The relevant portions of the codebook and instructions are available in the supporting materials. For each enactment, I code whether it was an act of Congress, the President, an administrative agency or department, or a court. I also categorize it by issue area based on the PAP issue area codebook. I code all policy histories for the factors that each author judged significant in each policy enactment. To capture their explanations, I have coders ask themselves 61 questions about each author’s explanation of each enactment from a codebook. Based on these questions, I record dichotomous indicators of whether each author’s explanation included each factor for every significant change in policy that they analyze. The supporting materials include the relevant factors included in the content analysis classified into the categories used here. Coders of the same volume reach agreement on more than 95% of all codes. In the results below, I aggregate explanations across all authors, considering a factor relevant when any source considered it part of the explanation for an enactment. Most authors rely on their own qualitative research strategies to identify significant actors and circumstances. For example, the books that I use quote first-hand interviews, media reports, reviews by government agencies, and secondary sources. I rely on the judgments of experts in each policy area, who have already searched the most relevant available evidence, rather than impose one standard of evidence across all cases and independently conduct my own analysis that is less sensitive to the context of each policy debate. Collectively, however, policy historians likely still have biases that are reflected in their focus. These biases, if similar across scholars, also inevitably color the aggregate content analysis. The policy histories therefore offer a useful comparison to current theoretically focused research on the policy process, but not a definitive test of their claims.I also record every individual and organization that was credited by policy historians with bringing about policy change. For each policy enactment mentioned by each author, I catalogue all mentions of credited actors (proponents of policy change that were seen as partially responsible for the enactment). I then combine explanations for the same policy enactments, aggregating the actors that were associated with policy enactments across all authors. The typical explanation credits the few actors most responsible for each policy change. Coders of the same volume reach agreement on more than 95% of actors mentioned as responsible for each enactment. I also count the number of members of Congress, interest groups, and government organizations credited with policy enactments in each issue area and categorize the actors ideologically, based on whether they were Democrats (or liberal organizations) or Republicans (or conservative organizations). I use affiliation networks to understand the structure of relationships in each issue area. These networks include all of the actors that were partially credited with a policy enactment in each issue area, with undirected ties based on actors that were jointly credited with the same policy enactments. This does not necessarily indicate that the actors actively worked together, but that they were both on the winning side of a significant policy enactment and that a policy historian thought they each deserved some credit. The affiliation network ties are valued as integer counts of the number of shared policy enactments between every pair of actors.To assess the extent to which differences across issue areas can be easily summarized, I use nonmetric multidimensional scaling and k-means cluster analysis (see Everitt et al. 2011). First, I construct a dissimilarities matrix between all pairs of issue areas based on their differences on the number of enactments in each venue, the percentage of enactments associated with each causal factor, and the characteristics of each issue network. I then place the issue areas in dimensional space and clusters. The goal is to see whether typologies can account for issue area differences.Policy Enactments Across Issue AreasPolicy is enacted in every branch of government and issue area, though hardly with equal frequency. Figure 1 depicts the number of significant policy enactments in each issue area in each venue since 1945, separating laws passed by Congress from executive orders by the president, administrative agency rules, and court decisions. Unsurprisingly, Congress dominates policymaking in most issue areas. Nevertheless, a few issue areas stand out for the extent to which policy enactments occur in other branches of government. In civil rights, criminal justice, and finance & commerce, policymaking occurs disproportionately in the judiciary. Enactments in the energy and science & technology domains are more likely to come from administrative agencies. [Insert Figure 1 Here]Policymaking in each issue area also differs dramatically in its frequency: health and the environment are associated with more policy enactments. This is partially a consequence of their consistent prominence on the government agenda. The correlation between the total policy enactments in each issue area and the number of congressional hearings over the entire period is .49. Transportation, however, is regularly on the agenda without producing many policy enactments. Issue areas also differ substantially in the extent to which their policymaking is path dependent or episodic. Figure 2 compares the percentage of policy enactments where policy historians referred to factors related to path dependence with the percentage of enactments where they pointed to particular events driving policy change. This does not indicate that the historians used any language related to the theoretical concepts of path dependence or focusing events; most did not. Instead, explanations involving path dependence included any statement that the enactment was an extension of an earlier policy, that an earlier choice made the enactment more likely, or that an earlier choice eliminated a potential alternative policy. Explanations involving events pointed to the effects of war, economic downturn, a government financial problem, a focusing event such as a school shooting, or a case highlighting problems in a previous policy. [Insert Figure 2 Here]The results show that policy enactments in agriculture, energy, housing, and labor are most likely to be path dependent. Enactments in energy and macroeconomics are most likely to be associated with events, especially nuclear disasters and economic downturns. These two potential sets of explanatory factors do not directly trade-off with one another. Some policy changes were not associated with either category of factors. Others were associated with both past policy choices and focusing events, such as reauthorization of an environmental statute in response to a natural disaster. Nevertheless, more episodic policy areas were associated with more congressional hearings. The number of hearings in each issue area is correlated at .46 with the difference between the percentage of enactments that were episodic and path dependent. Analyzing the policy agenda may thus track episodic issue areas while missing significant enactments in areas with more path dependence. Reported Circumstances Responsible for Policy EnactmentsPolicy histories also point to somewhat different types of circumstances in explaining policy change in each area. Table 1 reports the percentage of policy enactments in each issue area associated with six categories of causal factors. These categories are not mutually exclusive or exhaustive. They were the external circumstances mentioned by policy historians most often and are common components of theories of the policy process. Explanations involving media coverage point to general attention or specific articles. In the public opinion category, I include references to public views, issues raised in an election campaign or by constituents, or a public protest. Explanations involving interest groups include advocacy by non-governmental organizations, business interests, professional associations, or unions. Those involving international factors include references to foreign examples and international pressure or agreements. Explanations involving state or local factors include references to state or local actions that preceded federal action or reports from state or local officials. For explanations involving research, I include references to data or research findings, think tank or academic involvement, or research reports. [Insert Table 1 Here]Media coverage was most commonly associated with policymaking in macroeconomics, the environment, social welfare and transportation. Reports of pollution, poverty, and dilapidated infrastructure all play roles in policy development. Public opinion was a commonly reported cause of enactments in macroeconomics, civil rights, and labor and significantly less common in energy, finance, and science. Public concern over economic conditions, for instance, was regularly credited with macroeconomic policy change. Interest group influence was quite common in most issue areas, but was significantly more common in agriculture, transportation, the environment, and civil rights. Historians regularly credit lobbying by industry groups in agriculture and transportation as well as advocacy by public interest groups for civil rights and environmental protection. Science & technology policy registered the highest rate of international influence, with the Soviet launch of Sputnik serving as the most prominent example. State or local influence on policy enactments was most common in the areas of housing and civil rights but was significantly less common in science and agriculture. According to policy historians, factors related to research were commonly associated with policy change in most issue areas, with the exception of civil rights. Policy historians regularly cite new data as well as summary reports from government agencies as factors in policy change.The Diversity of Issue NetworksPolicy histories also credit particular individuals and organizations with bringing about policy change in each area. The networks that I analyze enable a visualization of the relationships among these actors. Figure 3 depicts a sample of four issue networks. Nodes are actors credited with enactments; links connect actors credited with the same enactments. Black nodes are Democrats or liberal organizations; white nodes represent Republicans or conservative organizations; others are grey. Actors in the legislative branch are represented as circles; actors in the executive branch are squares; diamonds represent those in the judicial branch and triangles are non-governmental actors.[Insert Figure 3 Here]There is remarkable variation in the composition and structure of networks across issue areas, though none resembles a hollow core. None of the issue areas have a clearly bifurcated network polarized by ideology, though there are differences in degree. There is also substantial cross-branch interaction in most, but not all, issue areas. Table 2 reports several characteristics of the composition of each issue area’s network. Members of Congress dominate half of the networks and interest groups dominate two of the networks; others have a mix of central players. Organizations like executive agencies are central in the transportation network.[Insert Table 2 Here]Table 3 reports common characteristics of the structure of each issue area’s network. Size is the number of actors. Density is the average number of ties between all pairs of actors. In this case, the interpretation is the average number of policy enactments for which each pair of actors in the network shared credit. Paul Hallacher (2005) uses equivalent notions of size and interaction to compare subgovernments and issue networks, suggesting that issue networks have high values for each. The core-periphery model in Table 3 compares each network to an ideal type in which a central group of actors is closely tied to one another and surrounded by a periphery of less connected actors. The fitness statistic reports the extent to which the network fits this ideal type; the core density statistic reports the density within the group of actors identified as the core of the network (a categorical distinction). High values here would indicate that a network is far removed from the “hollow core” that characterized some previous networks (see Heinz et al. 1993). [Insert Table 3 Here]Degree Centralization measures the extent to which all ties in the network are to a single actor. The Clustering Coefficient measures the extent to which actors that are tied to one another are also tied to the same other actors. Table 3 also reports two versions of the E-I (external-internal) index to track cross-branch and cross-party ties. The index measures the extent to which ties are disproportionately across groups (positive) or within groups (negative). The groups for the first index are actors in Congress and those in the executive branch; for the second, the groups are Republicans or conservative organizations and Democrats or liberal organizations. Issue networks differ in their structure across issue areas. Some networks are large and dense like transportation, whereas others are small and dense like agriculture. The health network is large but sparse but science is small and sparse. The issue networks that most resemble the core-periphery structure are civil rights and the environment. The most centralized networks are housing (around the U.S. Conference of Mayors) and labor (around the AFL-CIO). Clustering is most evident in the environment and least evident in energy. The networks most polarized by partisanship are the environment, science, and civil rights. The networks with most ties between the legislative and executive branch are housing, finance, and macroeconomics; civil rights and science had the least cross-branch oriented networks. Dimensions of Issue Area PoliticsTo evaluate the number of underlying dimensions of issue area politics and to see where issue areas sit relative to one another on these dimensions, I use nonmetric multidimensional scaling. This provides two kinds of output: information about how well a model with each number of dimensions fits the data and a scale score for each case on each dimension. A typology that successfully made sense of the differences in politics across issue areas would require differences to be summarized by a small number of dimensions where the cases clearly separated into clusters. Figure 4 depicts a multidimensional analysis of issue area dissimilarities, using the characteristics of policy change reported in Figures 1 and 2, the reported circumstances associated with policy change from Table 1, and the characteristics of issue networks from Tables 2 and 3. Although the model is depicted in two dimensions, the results suggest no clean break in the number of dimensions. The measure of Stress_1, a fit statistic where lower numbers indicate a better fit, is .075 for a one-dimension solution, .037 for a two-dimension solution, .016 for a three-dimension solution, and .003 for a four-dimension solution. [Insert Figure 4]I also use k-means cluster analysis to divide the issue areas into clusters based on the same dissimilarities. The Calinski-Harabasz and Duda-Hart procedures (see Everitt et al. 2011) for determining the appropriate number of clusters were inconclusive, with the former producing improved fit statistics with 3 and 13 clusters and the latter producing improved fit statistics with 4 and 5 clusters. A two-cluster solution divides agriculture, crime, energy, finance, and science into one cluster (the issue areas on the right side of Figure 4). One interpretation is that these issue areas are associated with less popular mobilization whereas the others involve broader economic and social policy agendas. An alternative three-cluster solution separates crime into its own cluster from this group. A four-cluster solution has a separate cluster for agriculture and for civil rights and labor. Beyond this number, the algorithm begins separating each issue area into a unique cluster. Rather than clean categories, distinctions among issue areas are best seen as continuous differences. The results suggest that there is no easy way to summarize the differences across the political processes surrounding each issue area and their associated issue networks. A two-by-two typology, for example, would have an especially poor fit with the data. We cannot be sure that two dimensions best account for issue area differences, that the issue areas divide cleanly along those dimensions, or that four clusters would be the most appropriate division. I also analyze several reformulations of the data to ensure that the results were not a product of methodological decisions. First, I divide the data across time into subsets of 15-year periods and searched for an underlying structure. Second, I categorize the issue areas into a larger number of subtopics, each covering a smaller territory. Third, I analyze only the policy enactments considered significant by most authors in each area and limit the explanatory factors considered to only those with consensus across authors. Fourth, I construct distinct sets of dissimilarities based on network characteristics and based on the factors reportedly driving policy change. Issue area differences did not produce clear clustering on a few underlying dimensions in any of these analyses. Some readers may interpret the findings as evidence that there are large differences among the scholars studying these issue areas, rather than the issue areas themselves, but the evidence does not point in this direction. First, authors covering policy enactments outside of their area of focus (such as health policy historians explaining the political process behind general tax laws) reached most of the same conclusions about who was involved and what circumstances were relevant as specialist historians. Second, there were few consistent differences in the types of actors credited and few differences in relevant circumstantial factors reported based on whether the authors used interviews, quantitative data, or archival research, whether the authors came from political science, policy, sociology, economics, history, or other departments, or how long after the events took place the sources were written. There were idiosyncratic differences across authors, but they did not produce the differences across issue areas.Making Sense of Issue Area Similarities and DifferencesThere are some seemingly universal features of the policy process, but there are also important differences in each issue area’s politics. The 14 domestic policy areas analyzed here differ in their frequency of policymaking, their common venues, the circumstantial factors enabling policy change, the actors responsible for enactments, and the structure of networks. On each dimension of issue area differences, most issue areas fall in the middle rather than at the extremes. Policy typologies are unlikely to isolate the different features of policymaking in each issue area. Indeed, the available policy area typologies are not predictive of the differences analyzed here. Theoretical distinctions made by Lowi (1964) and Wilson (1980) are not helpful in distinguishing among the types of politics present in each issue area. Distinctions between iron triangles, issue networks, and policy communities are equally unhelpful. This is a sign that the theories that produce typologies should be subjected to more scrutiny. The project of creating minimalist models of the policy process based on ideal types may not be helpful. The iron triangle ideal type, for example, mixes three independently varying dimensions of network structure: a strong core, cross-institutional links, and bipartisan links. Instead of assuming that issues will fall clearly into boxes, scholars should acknowledge that issue area differences are widespread but not very amenable to categorization. Table 4 lists descriptions of the features of each issue area that stand out when compared to the others, including the type of policymaking, the circumstances associated with policy enactments, and the composition and structure of the governing network. All policy areas stand out in some ways in comparison to the others. This comparative analysis should enable authors of case studies to check whether their findings are likely to apply only to a few issue areas or generalize to the policy process as a whole. [Insert Table 4 Here]There are also important similarities in policymaking that are reportedly common across issue areas, even though I rely on 14 distinct literatures on a broad spectrum of domestic policy. First, Congress is the most frequent maker of significant policy in nearly all issue areas and it is responsible for the bulk of policymaking in most areas. Second, all policy areas have some policy enactments where path dependent explanations are apt and others where event-related explanations are apt. Third, interest groups and research reportedly play a common role in policymaking in most issue areas whereas public opinion and media coverage play less frequent roles. Fourth, all issue areas are associated with networks of actors credited with policy change, including members of Congress, executive branch agencies, and interest groups. These similarities are generally consistent with the textbook treatments of federal policymaking that focus on institutions.The issue area differences, however, have important implications for the generalizability of research findings. Issue area case selection decisions make large differences in likely findings. For example, Kingdon’s (2003) study of the policy process is based on case studies of health and transportation. If he had instead chosen to study education and labor, he might have shown more influence for public opinion and international factors. Likewise, because a great deal of scholarship using the ACF focuses on environmental policy (Weible, Sabatier, and McQueen 2009), scholars may be more likely to find influence by interest groups and research. The results may also show where each of the policy process frameworks could be productively applied. The research and coalition focus of the ACF, for example, might be useful in studies of agriculture and housing. The focus on episodic determinants of policy change in PE studies has been useful in studies of nuclear energy and budgets (Jones and Baumgartner 2012). This comparative research shows that energy and macroeconomic policies more broadly are the most likely to be associated with episodic causes of policy change. Theories of path dependent policymaking, in contrast, may be most appropriate in agriculture, education, and housing.The findings also have implications for normative discussions of the policy process. Scholars who sought to divide policymaking into categories (e.g. Wilson 1980, Lowi 1964) associated their typologies with judgments about the relationship between the policy process and democratic values. If issue area politics cannot be easily predicted based on whether policies tend to benefit majorities or minorities, general claims about where policymaking is likely to be more or less democratic may not hold up to scrutiny. Similarly, politics in every issue area may be labeled “interest group politics” to some degree, even though groups are not the only important actors in any area.Claims about iron triangles and issue networks were also meant to raise concerns that policymaking did not live up to America’s founding principles. Iron triangles supposedly involved domination of policymaking by political insiders. Heclo (1978) also viewed issue networks with concern, arguing that they came with a “democratic deficit” because they empowered technocratic elites. Disproportionate involvement by administrators and scientists, however, is only one source of difficulty in matching our expectations of wide participation with the reality of the policy process. Disinterested citizens representative of the nation as a whole do not make up any issue networks. Instead, each issue area is associated with distinct distributions of political elites. Despite differences across issue areas, there is potential ground for general theories of the policy process and associated critiques of the relationship between democracy in theory and practice. Across the issue areas analyzed here, all issue areas involved multiple institutions, interest groups, and diverse policymakers. They incorporated several circumstantial factors and responded to both past policy development and current events. There are many factors in the policy process but some are much more frequently influential than others. Issue area differences are decipherable and should be emphasized, but the similarities in the relative importance of each component of policymaking across issue areas are just as important. The American national government has both a general policy process and some unique variants for each issue area.ReferencesBaumgartner, Frank R. and Bryan D. Jones. 1993. Agendas and Instability in American Politics. Chicago: University of Chicago Press.Berry, Jeffrey. M. 1989. The Interest Group Society, 5th ed. New York: HarperCollins Publishers.Everitt, Brian S., Sabine Landau, Morven Leese, and Daniel Stahl. 2011. Cluster Analysis, 5th ed. 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Boulder, CO: Westview Press.Table 1: Reported Circumstances Associated with Policy Enactments in Issue Area HistoriesMedia CoveragePublic OpinionInterest GroupsInternationalState or LocalResearchAgriculture18.42%21.05%63.16%13.16%0%47.37%Civil Rights & Liberties21.31%31.15%67.21%11.48%24.59%22.95%Criminal Justice25%30.77%30.77%0%9.62%42.31%Education12.12%27.27%48.48%12.12%18.18%42.42%Energy18.18%13.64%36.36%13.64%18.18%31.82%Environment29.9%25.77%69.07%12.37%19.59%54.64%Finance & Commerce10.34%6.9%36.21%3.45%5.17%22.41%Health10.53%11.58%36.84%7.37%9.47%38.95%Housing & Development16.67%13.89%58.33%0%19.44%44.44%Labor & Immigration16.07%30.36%55.36%10.71%12.5%37.5%Macroeconomics22.92%41.67%54.17%14.58%8.33%41.67%Science & Technology7.89%7.89%36.84%23.68%2.63%28.95%Social Welfare 22.22%22.22%38.89%0%13.89%36.11%Transportation22.22%17.78%57.78%0%6.67%31.11%The table reports the percentage of enactments that involved each factor, according to policy historians. Table 2: Issue Area Governing Network CompositionMost Central (Degree)Dominant TypeCongress MembersInterest GroupsGovernment Orgs.#Links#Links#LinksAgricultureAg. Dept, Farm BureauCongress179.989.966Civil Rights & LibertiesNAACP, JFK, MLK Jr.Int. Groups6320.4524.91623.1Criminal JusticeACLU, Bar Assoc.Int. Groups206.7168.4117.2EducationEdith Green, NEACongress5419.52716.11516.1EnergyFord, Ted KennedyCongress205.3124.192.4EnvironmentEd Muskie, J. BlatnikMixed3613.1347.23313.1Finance & CommerceEisenhower, LBJCongress193.43373.1HealthTruman, Mary LaskerCongress469.7319.9268.7Housing & DevelopmentU.S. Conf. of MayorsMixed399.72914.6229.5Labor & ImmigrationAFL-CIO, Labor Dept. Mixed7614.86317.42416.5MacroeconomicsWilbur Mills, TreasuryCongress4211.61215.21620.4Science & TechnologyFCC, NixonMixed122.8122.8134.7Social WelfareWilbur Mills, Social SecCongress4511.42412.71816.7TransportationFord, Ted KennedyGov. Orgs.2416.12918.63020.8The table reports characteristics of the actors credited with policy enactments in each issue area. Table 3: Issue Area Governing Network Structural CharacteristicsCore-PeripheryE-I IndexSizeDensityFitnessCore DensityDegreeCentralizationClustering CoefficientCongress-Admin.BipartisanAgriculture490.170.70.889.50%1.02-0.11-0.14Civil Rights & Liberties2100.10.691.077.21%1-0.34-0.28Criminal Justice830.080.52110.52%1.02-0.5-0.17Education1700.10.470.629.83%0.97-0.14-0.23Energy650.070.5915.96%0.91-0.18-0.28Environment1440.090.684.397.74%1.2-0.21-0.42Finance & Commerce540.060.481.054.34%0.99-0.03-0.03Health1410.070.491.176.60%1.01-0.28-0.01Housing & Development1190.10.480.8715.50%1-0.07-0.23Labor & Immigration2110.10.490.8414.18%1.14-0.06-0.19Macroeconomics1180.120.671.079.94%1.06-0.02-0.01Science & Technology700.060.2924.38%0.98-0.38-0.29Social Welfare1360.10.561.048.06%1.07-0.13-0.24Transportation1270.190.761.2913.48%1.12-0.13-0.15The table reports structural characteristics of the affiliation networks associated with policy enactments in each issue area.Table 4: The Relative Features of Each Issue Area’s PoliticsType of PolicymakingRelevant CircumstancesNetwork CompositionNetwork StructureAgricultureRegular, path dependent enactmentsHigh interest group influenceSmall, mostly congressional networkDense core-periphery networkCivil Rights & LibertiesMulti-branch, frequent, and path dependentHigh state/local influence but low research influenceLarge network with many interest groupsCore-periphery structure but low centralizationCriminal JusticeDisproportionately judicial enactmentsHigh research influence but no international influenceSmall network with central interest groupsExecutive-congressional divideEducationPath dependent enactments by Congress No dominant influential factorsLarge network dominated by members of CongressCore with satellite clustersEnergyDisproportionately administrative, event-driven Low public opinion and high state/local influenceSmall network, concentrated in CongressLow centralizationEnvironmentMany enactments with congressional dominanceHigh media, state/local, and research influenceDisproportionately Democratic networkDense core with high clusteringFinance & CommerceSplit policymaking between Congress and courtsLow research influenceSmall, congressional and presidential networkSparse decentralized networkHealthMany enactments in CongressNo dominant influential factorsLarge network, dominated by members of CongressSparse tiesHousing & DevelopmentPath dependent enactments in CongressHigh state/local, low public opinion influenceLarge diverse networkCentralized network with partisan divideLabor & ImmigrationMulti-branch enactmentsHigh public opinion and group influenceLarge, diverse network, centralized on AFL-CIOSparse network, with high clusteringMacroeconomicsEvent-driven, legislative enactments High public opinion and research influenceCongress-dominated networkDense network with high inter-branch/bipartisan tiesScience & TechnologyDisproportionately administrative enactmentsLow public opinion but high international influenceDiverse, with many government organizationsSparse, disconnected network with no coreSocial WelfareInfrequent, path dependent enactmentsHigh media but no international influenceCongress-dominated networkLarge divided networkTransportationRegular congressional enactmentsHigh interest group, no international influenceLarge diverse network, with government organizationsDense core-periphery network; high clusteringThe table reports descriptions of where each issue area stands out among the others, based on the analysis of policy area histories conducted here. Figure 1: Policy Enactments by Venue and Policy AreaThe figure depicts the number of policy enactments in each branch of government from 1945-2004, based on policy histories of each issue area.Figure 2: Developmental and Episodic Reported Causes of Enactments by Policy AreaThe figure depicts the percentage of policy enactments in each issue area that were reportedly affected by path dependence (including earlier policy choices that made the enactment more likely or eliminated alternatives) and focusing events (including wars and economic downturns). The reports are based on policy histories in each issue area covering significant policy enactments from 1945-2004.Figure 3: A Sample of Issue Networks EducationLabor Social WelfareTransportationNodes are actors credited with policy enactments in each area. Links connect actors credited with the same policy enactments. Democrats are black; Republicans are white; others are grey. Shape represents branch of government; circles are legislative; squares are executive; diamonds are judicial; triangles are non-governmental. Figure 4: Nonmetric Multidimensional Scaling of Dissimilarities Among Issue Areas The figure is a two-dimensional plot of nonmetric multidimensional scaling results of dissimilarities based on the reported factors in policy change since 1945 and the characteristics of their issue networks. The dissimilarities are based on the characteristics of issue areas reported in Figures 1-2 and Tables 1-3. ................
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