The readings this week explore the various models involved in the decision making process. Howlett and Ramesh in Chapter 6 of ‘Studying Public Policy: Policy Cycles and Policy Subsystems, maintain “that choosing a solution to a public problem or fulfilling a societal need does not even remotely resemble the orderly process proposed by some analyst”. Lindbolhm (1959) in ‘The Science of Muddling Through’ distinguishes between ‘root and branch’ approaches to policy formulation while Foster (1984) in ‘Bounded Rationality and the Politics of Muddling Through’ provides a discussion of the comprehensive and the bounded rational approaches to public decision-making. In this short paper I provide a brief discussion of the various approaches to the public administration and apply it to US immigration policy.

Lindbolhm (1959) and Foster (1984), both examine the policy making process in terms of two separate alternatives. Lindbolhm describes the ‘root’ or rational comprehensive approach in five points: clarification of objectives, isolate the ends then seek the means, effective policy then is based on the selection of the best means, every important relevant factor is taken into account, and heavy reliance on theory. This he contrasts with the ‘branch’ or what Foster (1984) calls the bounded rational approach also summarized in five points: selection of value goals that are closely related, very limited means-end analysis, good policy is typically agreed upon, limited analysis which ignores alternative outcomes, policies and goals, and reduced reliance on theory. ‘Muddling’ through policy making then involves the implementation of strategies appropriate to the specific context and dependent on the contextual complexity of the decision making process. Both authors seem to agree that ‘Muddling Through’ is the most practical approach to policy making as it gives administrators the flexibility of adjusting strategies based on need.

The design of Immigration policy here in the US has been an extremely controversial subject, and as the first African American president enters his second term it seems an issue that will be focused on intensely in the coming year (2013). In a country of immigrants it is not difficult for one to understand why immigration policy is a highly controversial subject. With politicians often violently disagreeing on this issue, by-partisan consensus is indeed a welcomed occurrence. Perhaps illustrative of the “muddling through” involved in public policy formulation, the history of immigration policy in the US has been characterized by persistent reform as policy makers continuously seek to find better ways to deal with this policy issue. The latest round of debate involves the provision of a path to citizenship for the 11 million unskilled workers who currently reside illegally in the US. As well as the ‘softening’ of immigrations laws to allow skilled workers who have acquired advance training in the US to stay. Then there is the issue of the right of American citizens and permanent residents to sponsor their same sex partners which policy specialist believe will garner very little popular support but is definitely part of the President’s reform plan.

The current President is perhaps one of the most progressive liberal democratic leaders of the US in decades and has already passed the ‘Dream Act’ which provided a path for citizenship for millions of young people who were currently in the US illegally because they were brought here as children but had acquired high school education. As one examines the evolutions of the US Immigration policy a pattern emerges that can not be described as rational comprehensive or originating from some ‘root’ source. Rather this pattern involves successive restructuring of policies to cater to the specific context and complexity of the situation. For example the Immigration Reform and Control Act was in-acted in 1986 primarily to deal with the problem of the large number of illegal immigrants who had resided in US since 1982. A few years later the Immigration Act of 1990 was passed but while this law did not focus on illegal immigrants its main concern was to clearly define categories for legal immigration and expand the annual numbers of legal immigrants into the US. Coincidently this reform occurred at a time when demand for highly skilled workers was on the rise. The same can be said for the recent STEM act that provides incentive for students who have obtained Science, Technology, Engineering and Math degrees. Or the amendments that provided Visas for increased numbers of teachers and health professionals.

Indeed immigration policy here in the US can surely be described ‘muddled’ which seems to be the best direction for policy makers as they navigate this environment. I believe that this trend will continue as it is impossible to outline long-term objectives for immigration as well as the means for achieving these ends. It is simply an issue that continues to evolve and therefore the challenge for policy makers is find the best option to apply given the current cultural, political, social and economic environment.

Submitted by Deon Gibson


References

Howlett and Ramesh, Chapter 6: “Public Policy Decision-Making.”

Lindblohm, Charles E., “The Science of ‘Muddling Through’,” Public Administration Review, 19(2), 1959

Forester, John, “Bounded Rationality and the Politics of Muddling Through,” Public Administration Review, 44(1), 1984.

            The past half-century has witnessed the emergence of a large body of literature devoted to the issue of decision-making process in policy. At the center of this methodological discussion are the notion of rationality and the question of how policy decisions are being made. Rationality -- as understood by neo-classical economics – has been often perceived as value-free and objective.[1]  Under this premise, policy makers carefully weight the pros and cons, evaluate the means and define the objectives of a given policy. But even if we agree with this narrow definition of rationality, we can always wonder to what extent this rational model provides an adequate explanatory framework for decision-making?  Indeed rational choice, although still dominant in the policy analysis literature, has been widely contested for its capacity in assessing decision-making in “real world” policy environments. 

Lindblohm (1959) and Forester (1984) draw our attention to the fact that during the decision-making process rational choice is often an optimal condition that is rarely achieved. For Lindblohm, the complex problems and decisions of public administrators stumble across disagreements on nebulous values and objectives. In this sense, the policy maker rarely operates under optimal-rational conditions.  More so, the realities of decision-making are grounded on what Lindblohm calls “the science of muddling through”, an incremental process that relies upon modest step-by-step comparisons. Perhaps the merit of Lindblohm analysis relies not only on the critique of the rational model but also in the fact that it recognizes continuity in the policy-making process. Following his branch-incremental instead of root-rational method, one can detect the underlying notion of path dependency in policy making.

Forester, departs from Lindblohm’s “muddling through” concept in order to establish several gradients of “boundedness” in rational decision-making. He determines a scale of increasing complexity (from the one-actor comprehensive and unbounded scenario to the cognitive, socially differentiated, pluralist and structurally distorted bounded rationalities) in the decision-making and emphasizes how the context greatly affects the decisions and strategies adopted. He concludes, “If practical strategies are context dependent and contexts in practice vary widely, always changing, then rational action and decision making will fail in a technical search for a one-best-recipe. Instead of recipes, repertoires of strategies are called for-and should be investigated in diverse decision-making situations.” (1984:30).

Perhaps the failure of the one-best-recipe that Forester refers to, crystalized in the policy world during the Washington Consensus era and the implementation of structural adjustment policies (SAPs) that took place in several developing countries in the 1980s. In recent years, many scholars have criticized these policies as neglecting the specific country context and focusing on first-best thinking. Indeed, SAPs were founded on the conviction that we can always approximate the conditions under which Pareto optimums are possible by simply applying appropriately targeted remedies and policy reforms based on rational economic thinking. But as Rodrik reveals in One Economics Many Recipes the striking feature of the economic growth after the SAPs period is that the most successful economies (China, South Korea, Taiwan, Mauritius etc) among developing countries adopted policies that look quite different than the rational first-best reforms formulated under the various SAPs.  

Certainly, this realization has implications on the legitimacy of the rational approach in decision-making.  While, there is no denial that the “root method” can provide a valid intellectual framework, is it appropriate in encompassing the complex contextual environment of decision-making? Forester argues that rationality is not an abstract notion but one that morphs along specific informational and contextual parameters. He argues that policy makers “do what they can” in a given situation. Perhaps his view offers a more realistic understanding of the complexities of the policy process and provides further understanding on the acute antagonisms and the difficulties of implementing policy recommendations.

Ultimately, through their critiques of the rational model, both Lindblohm and Forester offer a multi-dimensional analytical lens of the policy process. Their analysis has repercussions on the ways we think about decision-making; not as isolated decisions based on a mere aggregation of personal preferences but as a societal process involving power dynamics, cooperation and conflict between the different actors involved in the policy process.

Achilles


[1] Simon argues, that the perception of rationality in neoclassical economics differs from the other social sciences in three main respects: (a) in its silence about the content of goals and values;( b)in its postulating global consistency of behavior; and (c) in its postulating "one world"-that behavior is objectively rational in relation to its total environment, including both present and future environment as the actor moves through time.

Andrea

The disconnect between theories and models, and the practice of policymaking formed the central tenet of the discussions presented in this week’s readings. This finding is certainly not revolutionary; in the US, countless major policy reform efforts have failed due to lack of realistic vision from policy analysts, who assume that policymakers, legislators, lobbyists, and the public will act in a “rational” capacity, in accordance with the requirements of the rational model (Etzioni, 1967, 385; Howlett, 2009, 145; Munger, 2000, 6). Policy analysts and theorists don’t have to dig deep to find that rational thinking rarely dictates how policy decisions are made, or gain advocates or critics.

In the US, the majority of policy decisions are not made by direct referendum; voters elect legislators whom they think will best represent their own social and economic interests and support the implementation of corresponding laws and policies. As in most (all?) democracies, the basic principle is that the majority rules: each district, state, etc., in theory elects officials that best represent the political interests of the majority. In national elections, the totality of state’s electoral votes reflects the political preferences of the majority of the population.  This seems, yes, rational.

Yet, the successful reelection of Obama, and the consistent low poll ratings of the Republican party have prompted a rethinking among some legislators of how the electoral college functions and how electoral votes are allocated. In New York magazine, Jonathan Chait reports on a new policy idea being floated among Republican legislators in states that went blue in the 2012 national election. He finds that while Virginia, Michigan, Wisconsin, Pennsylvania, and Ohio voted for Obama, Republicans control the state governments; governors, senators and congressman from these states have proposed new policy measures that would allocate electoral vote not “as a lump sum to the candidate who gets more votes, but piecemeal, to the winner of each congressional district” (Chait, 2013). Under this proposal, “Wisconsin, where Obama won by 7 percent, would have split its electoral votes 5-5,” and “Michigan, which Obama carried with 54 percent of the vote, would have given Romney nine of its sixteen electoral votes” (Chait, 2013).

 This impetus behind this policy proposal is not one might term “rational.” This reform is not intended to improve the functionality or equity of existing dysfunctional legislation; these legislators are acting out of self-interest, altering voting outcomes to favor their own political agenda. Electoral College alteration bills, like the one currently being floated in the Virginia State Senate, are being sponsored by legislators whose constituents are “discouraged by coming out because their votes don’t mean anything if they’re outvoted in metropolitan districts” (Chait, 2013). Phrased in this way, this policy proposal seems like a legitimate call for examining the effectiveness of the current electoral system, a concern echoed by Michigan House of Representatives speaker Jase Bolger, who said, that citizens from “various parts of the State of Michigan… don’t feel like their vote for president counts, because another area of the state may dominate that or could sway their vote” (Chait, 2013).

However, in practice, these legislators are seeking to allow the preferences of rural voters to be disproportionately represented by isolating their districts, and separating their votes from those in urban portions of the state, where the majority of the population lives. The political system already gives more power to people who live in low-population states. Voters in Wyoming have the same number of representatives in the US Senate as voters in California; this seems just, until you factor in the fact that California has about 66 times the population, let alone comparative analyses of each state’s contribution to GDP (Chait, 2013).

The fact that gerrymandering is being floated as a policy proposal, for the purpose of reinforcing political strongholds, demonstrates the disparity between the theoretical commitment of policymakers to “rationality” and their actual courses of action.

Sources:
-Chaite, Jonathan. “Who Needs to Win to Win?” New York. February 3, 2013. 
http://nymag.com/news/features/republican-party-2013-2/

-Etzioni, Amitai, “Mixed-Scanning: A ‘Third’ Approach to Decision-Making,” Public Administration Review, 27(5), 1967. (BB)

-Howlett, Michael and M. Ramesh. Studying Public Policy: Policy Cycles and Policy Subsystems, Oxford University Press, 2009 (3rd Edition).

-Munger, Michael C. Analyzing Policy: Choices, Conflicts and Practices, W.W. Norton & Co., 2000.

Zoé Hamstead

In 2010 the Affordable Care Act was passed into law amidst a great deal of controversy, marked by numerous lawsuits that were filed in the wake of its adoption. While many of these lawsuits have been resolved and courts have more or less upheld the act, one issue which has not been definitively settled is to what extent religious freedom may exempt employers from particular health care provisions – namely, the coverage of birth control for women. Some religious employers believe that some forms of birth control constitute abortion and any action that increases access to such services constitutes immoral behavior. As part of a broader and in many ways controversial policy framework involving multiple actors, we can examine the policy-making process of the birth control coverage policy in reference to the stages model of policymaking and its criticisms.

Beginning with Harold Lasswell in 1971, public policy scientists have proposed variations of the stages model of policymaking to describe the public policy decision-making process. With its emphasis on process, this model theorized a problem-oriented approach to decision-making, which helped to distinguish public policy science from political science and economics (Munger, 2000). Within this framework, in stage one a “decision-maker” would identify the “problem,” in this case, perhaps a lack of access to birth control. In stage two, decision criteria, such as the maintenance of religious freedom and/or comprehensive health care provision for the uninsured, are selected. Stage three would involve selecting and weighing alternatives, including 1) altogether excluding birth control from the menu of health care services that employers must provide, 2) requiring the provision of birth control from all employers regardless of religious mission, or 3) exempting some but not all employers. In step four, a decision-maker would consider policy constraints, such as further lawsuits and political backlash. Step five would involve implementation and studying the effects of the policy. How many women wanted to, but were unable to receive benefits? How many women paid out of pocket for birth control? What effects did the policy have on employers?  Though a defining theoretical framework, this rational-comprehensive approach has been criticized for being oversimplified, disjointed, unempirical and a generally inadequate description of the reality of decision-making.

Other approaches to studying decision-making view the processes as an incremental, “muddling through.” Lindblom (1959) argues that most non-technical, large-scale decision making happens through a process in which values and policies are selected simultaneously; goals and means are not distinct; good policy is defined by consensus across different values systems; and in which theory is rarely utilized. Under conditions of bounded rationality, decision-makers have limited time, limited resources, limited information and ill-defined problems. In the best case scenario, these conditions lead to satisficing as opposed to optimizing values; in the worst case they lead to the sacrifice of social justice for convenience (Forester, 1984).

Under Lindblom’s successive limited comparisons model, the choice to value religious freedom more than affordable access to birth control is inseparable from the choice of the policy. Although a decision-maker may [somehow] abstractly value access to health care more than any other goal, the ultimate choice to exempt some employers due to feasibility constraints constitutes an implicit value weighting. Success of the policy is judged based on whether women’s rights advocates, religious groups and health care advocates, among others, will encourage constituents to vote for democrats, stop waging lawsuits, and be otherwise appeased. Under conditions of unequal power distribution among these groups, some groups may shape the policy more than others.

A major limitation of the incremental decision-making framework is that the role of a broader policy context may be ignored (Etzioni, 1967). Specific policies of the Affordable Care Act are made in the context of broader policy concepts such as the separation between church and state and the Roe v. Wade decision, which set a legal precedence for disallowing most restrictions on abortion in the U.S. Without the Roe v. Wade legal precedence, would the Obama administration have attempted a health care provision that some religious groups consider akin to providing abortion? Without precedence for the protection of religious freedom, would Hobby Lobby have considered waging a law suit against the federal government? The administration’s current policy proposal is that insurance companies will cover health benefits of birth control in cases where non-profit religious employers object to its use. While in some sense this is an incremental decision made to strike a compromise among opposing groups, in another sense the proposal is an elaboration on more fundamental decisions that, while being continuously debated and revised, do in some sense provide an overall direction for the evolution of policy.  In enacting particular requirements of the Affordable Care Act, federal policy-makers need to not only consider the extent to which the goals of the act are met and how the process is structurally distorted, but also how these policies relate to the evolution of fundamental decisions which can influence future incremental decisions.

Etzioni, A. (1967). Mixed-Scanning: A “Third” Approach to Decision-Making. Public Administration Review, 27(5), 385–392.

Forester, J. (1984). Bounded Rationality and the Politics of Muddling Through. Public Administration Review, 44(1), 23–31.

Lindblom, B. C. E. (1959). The Science of Muddling Through. Public Administration Review, 19(2), 79–88.

Munger, M. C. (2000). Analyzing Policy: Choices, Conflicts and Practices. W.W. Norton & Company, Inc.

By Claude Joseph
The process of decision-making is by no means a clear-cut undertaking. There is no common ground among scholars on what should constitute the right method of policy-making. Some (such as Munger, 2000) propose an approach comprised of five main steps: 1) problem formulation, 2) selection of criteria, 3) comparison of alternatives and selection of the best policy, 4) consideration of political and organization constraints, and 5) implementation and evaluation of the program. This traditional framework known as the rational-comprehensive formulation of policymaking and inspired by the neoclassical economic paradigm has been a subject of a myriad of criticisms.

In his oft-cited article The Science of “Muddling Through,” Lindblom (1959) proposes a method of successive comparisons as opposed to the rational comprehensive framework. As he argues, the reason is simple.  The comprehensive rational perspective assumes unbounded intellectual capacities along with sources of information that men are far from possessing. Moreover, when time and money, two factors deemed necessary to address policy problems, are limited, the best way of doing is “adjustment at the margin.” Inspired by Simon’s bounded rationality approach, Lindblom develops a framework known as incrementalism, the essence of which is that “policy does not move in leaps and bounds, democracies change their policies almost entirely through incremental adjustment” (p. 84).

This line of reasoning, however, does not go unchallenged. Etzioni, among others, criticizes the “muddling through” approach for being too conservative. Thus, his Mixed-Scanning is, he contends, a combination of the rationalistic method and the incrementalist perspective while avoiding of being neither utopian as the former nor conservative as the latter. Whether Etzioni has achieved the goal he set forth in this article is really debatable. Forester (1984), on the other hand, in Bounded Rationality and the Politics of Muddling Through, outlines a somewhat more realistic approach. To him, context matters. In fact in decision-making, context indeed matters.

This morning, I received an email from Thomas Jacob, a fellow Ph.D student in charge of organizing academic events and the like so students can get together once a month in order to share their works, ideas and so on.  In his email, he says “If it’s not too much trouble, please shoot me a quick note with your class schedule. I’m going to combine them all in one place, to search for the optimal day/time to host our colloquia.” As it happens, in this specific context, it is highly likely for Tom to reach an optimal day/time because the number of students in this program is so small that a rational-comprehensive requirement can easily be met. If everyone shoots Tom a quick note with his/her class schedule, Tom, the decision-maker, will have complete and perfect information to undertake his operation.

However, should he aim at organizing an event to gather students from the whole school, the task would turn out to be very unlikely. Constraints would range from time-incompatibility among students to costs determination to organizational constrains, to mention just a few. This example, albeit not the most perfect one, conveys however the importance of context in decision-making.  Therefore, the first task in decision-making is to take into account the context within which the decision will be made. As Forester (1984) shows, the context involves elements such as the setting, the problem (whether or not it is well-defined, and whether its scope, value dimensions, and chain of consequences are clearly delineated), information (perfect or imperfect), and the availability of time. Once one has a clear grasp of the context, the determination of the appropriate method  – rational, incrementalism, mixed-scanning – of decision-making is feasible.

By Kelsey
Approaches of public policy vary regarding whether the researcher is defining the disciple as a science or describing the realistic environment of stakeholders, beneficiaries, policy makers, advocates, and various other actors that make up the policy process.  There is two dominate theories to the decision-making process that informs public policy: rational decision-making and incrementalism. Howlett and Ramesh (2009) present both of the theories in their book, with critiques of each position. Lindblom (1959) presents the incrementalistic approach as a muddling through of alternatives by policy makers and Forester (1984) sums up both frameworks and suggests environments when each would provide the most beneficial application. What I am left wondering is whether the process of decision making for public policy could benefit from an infusion of other disciplines like philosophy, history, psychology, sociology and anthropology as well as a realistic perspective from actual policy makers and actors. 

Howlett and Ramesh present the different forms of policymaking including the two most popular, rational decision-making and incrementalism. They argue that rational decision making provides a defined goal, explores all strategies to reach defined goal, knows no limits including time and all consequences to each strategy undertaken, and determines implementation strategy based on benefits outweigh costs. The strategy has been presented by several authors  (DeLeon, 1999) and provides a useful framework for decision-making by breaking down the process into steps, often employed by various actors and in an non-linear fashion, culminating in a process implemented.

Conversely, Lindblom, the father of the incremental approach, argues that in reality the policy process is a  “muddling through” of alternatives and is not as technical or process oriented as the former. He argues that each process involved in making policy are intertwined, often unrecognizable from the other, and policy makers just make due with what they have, limited intellectual faculties and all. 

Forester (1984) sums up the debate between the two points by concluding that each policy process, both incrementalism and the rational decision making policy, is applied in different situations. Variables such as number of agents, environment, framing of problem, information available and time available will determine the type of process the agent(s) utilize (Forester, 26).

These authors present decision-making processes, suggest when each process would provide maximum benefits, and add to public policy in important ways. Frameworks for policy-making processes are important, for different reasons to each side.  For one they are important for increasing efficiency, and others they might provide helpful guidance to include stakeholders and create “ownership” in beneficiaries to create sustainable solutions. However, I wonder whether the frameworks are indicative of actual practices and rely to heavily on business strategies than real relationship building practiced. Lindblom’s theory of “muddling through” may lack any prescriptive framework like that presented in the rational decision-making theory, yet  it provides a perspective into the “reality” of public policy that seems ignored in the other articles.

What I am left wondering is whether public policy needs an added perspective of reality, as behavioral economics has given to rational choice theory, and possibly other disciplines in order to truly come up with a working framework for policy making.  Interpretations of decision-making processes beginning with philosophical, historical, and psychological disciplines could inform a more in-depth analysis of the policy making process.

Resources:

Howlett, Michael and M. Ramesh. Studying Public Policy: Policy Cycles and Policy Subsystems, Oxford University Press, 2009 (3rd Edition).

DeLeon, Peter, Chapter 2: “The Stages Approach to the Policy process: What Has It Done?  Where Is It Going?” In Paul A. Sabatier Ed. Theories of the Policy Process, Westview Press,   1999.

Lindblohm, Charles E., “The Science of ‘Muddling Through’,” Public Administration Review,19(2), 1959.

Forester, John, “Bounded Rationality and the Politics of Muddling Through,” Public Administration Review, 44(1), 1984.

By Jmaine

In “The Stages Approach to the Policy Process,” P. deLeon (1999) argues that despite the few shortcomings of the stages approach, it is still a useful tool for providing quality analytic information to government. However, in “Mixed-Scanning: A 'Third' Approach to Decision Making,” A. Etzioni (1967) argues that the shortcomings of the rationalistic approach as well as the incrementalist approach warrant a new way. Etizioni proposes the mixed-scanning approach, which straddles the borderline of the rationalistic and incrementalistic traditions.

One of the key architects of the stages model is H. Lasswell. The stages model represents Laswell's vision for policy science, providing quality analytic information to government so it can solve public challenges. To solve public challenges, the stages model offers decision makers a process of seven steps: 1) intelligence, 2) promotion, 3) prescription, 4) invocation, 5) application, 6) termination, 7) appraisal. A student of Laswell later refined the framework, offering the list of a) initiation, b) estimation, c) selection, d) implementation, e) evaluation, and f) termination.

The stages model has a few strengths. One form of strength is that it brought some conceptual depth that was lacking in the conventional approaches of economics and political science. Another form of strength is that it shifted policy research from a concentration on public administration and institutions to a new foundation for solving problems. A third form of strength is that it allowed for the inclusion of 'social norms and personal values' in decision-making, which was often not made visible in economics and political science.

The stages approach also has a few weaknesses. Some of the strongest criticism comes from P. Sabbatier. Sabbatier points out that a) the model cannot offer a causal explanation for policymaking, b) it does not lend itself to hypothesis testing, c) it is an inaccurate description of how policymaking actually works, d) it overlooks the dynamic of inter-governmental relationships, e) it is a very paternalistic approach, i.e. 'top down,' f) it does not offer the prospects to include learning in the stages or address the fact that policy analysis may take on various roles.

In the end, deLeon appears to be agnostic but thinks that the stages model offers the most systematic approach. We have some idea of the parts of the whole, even though we may not have a very solid understanding of how the system works. DeLeon says we can take guidance from J.M. Keynes who wrote that “it is better to be roughly right than precisely wrong.”

A. Etzioni takes a broader approach to assessing the strengths and weaknesses of the stages model. Etzioni describes three analytic approaches that underpin decision-making. One model is the rationalistic approach, which assumes that actors “have a high degree of control over decision making situations” (Etzioni, 1967). In this approach, the actor is alerted of a public challenge, drafts a goal, develops criteria that can be used to evaluate alternatives, looks at the costs and benefits of each alternative, and makes a decision. The second model is the incrementalist approach, also known as 'muddling through' because it assumes that decision makers do not have a tight control over the policy environment. In this approach, the model runs on a couple of inputs: a) zero in on policies that offer incremental change, b) restrict the universe of policy alternatives to a few in number, c) when considering a policy, pinpoint just a few consequences, d) rely heavily on mechanisms such as analysis and evaluation, e) promote remedial policies that are geared towards meeting challenges of today, not the future. The third model is the mixed-scanning approach, which is a blend of those previously described.

To show us the difference between the three approaches, Etzioni uses one policy example. Imagine that the government was charged with setting up a global system (i.e. satellites) that would capture weather patterns. The rationalistic approach would set up an “exhaustive survey of weather conditions by using cameras capable of detailed observations and scheduling reviews as much as possible.” The problem with this approach is that it would have a high price tag and overload the possibilities for action. The incrementalist approach would use past observations as a guide to scan areas that are worth paying attention to. The problem with this approach is that the scan will miss the new developments in areas not covered by the scan. Finally, the mixed-scanning approach would “employ two cameras; one that covers all parts of the sky; another to focus on areas revealed to require more in depth examination.” The advantage of this approach is that it is well positioned to pick up on new developments should they arise. According to Etzioni, mixed-scanning is a more realistic and effective strategy to foster decision making.

Both Etzioni and deLeon promote a certain vision of the stages model. One limitation that was overlooked is that it does not fit how policy changes are happening at the local, state level. For five years, I tracked state legislation in Minnesota. There, the state legislature is a 'citizen legislature,' meaning that they meet for only four months out of a year. Between the start and end date of the legislative session, they must resolve a number of complex public challenges. In my experience, there was only three times where actual behavior was aligned with the stages framework. 1) I did notice that policy was initiated by voters, coalitions, or key stakeholders. 2) I also noticed that implementation was conducted at the state agency level, mostly after interpreting the meaning of policy guidance from lawmakers. 3) The only type of estimation (or impact analysis) that was done was fiscal notes. However, these fiscal notes hardly ever accounted for broader impacts, such as demographics (gender, race/ethnicity, age) or economic standing (low income) or inequality (disparities in opportunity or outcomes)—even though they were major dynamics of policy challenges.

The evaluation of policy hardly ever happened. I saw only two during my tenure, one on minimum wage, another on welfare to work. My representative lawmaker called for more evaluations but would face resistance because they take up a lot of time and cost to prepare. Transparency and openess are important stages not mentioned in the framework, something that J. Stiglitz (1998) would like to see more of in the public sector. I saw a lot of 'Lone Ranger decision-making,' closed door meetings where policy was hashed out and passed without regard for broader input or quality analysis. Can we strengthen the stages model by integrating how decision-making on state and local policy actually works? Is there another model that can complement the stages model?

References

DeLeon, Peter. 1999. “The Stages Approach to the Policy Process: What Has It Done? Where Is It Going? In Paul Sabatier Ed. Theories of the Policy Process. Westview Press.

Etzioni, Amitai. 1967. “Mixed-Scanning: A Third Approach to Decision-Making.” Public Administration Review, 27(5).

Stiglitz, J. 1998. “The Private Uses of Public Interests: Incentives and Institutions.” Journal of Economic Perspectives, 12(2).



Comment


I'm still a bit perplexed by Etzioni's use of the camera metaphor in his mixed-scanning model. After all, the mixed scanning approach seems very similar to the way the human eye works: we take a broad scan of the situation, and then zero in on areas that require additional examination (niches that present an opportunity or a problem, show new data or development, etc). We look at the entire mango tree, and zoom in on the ripest fruit on the most accessible branch. Just like Etzioni's qualifier, Managers zero in on areas requiring "higher level" attention (should the mango tree be pruned to encourage lower-hanging growth in the long term?), while workers focus on areas presenting problems to their specialty (How can I get all six of those mangos down without snapping that branch?). Opportunities for fundamental and incremental decisions can be seen with the human eye.

I wonder if this was an attempt to avoid references to biomimicry or evolutionary theory on Etzioni's part. Or, perhaps he intended to distance his metaphor from the human brain for more strategic purposes, if he did not intend to discuss the implication of serial or parallel attention span on the application of the camera's findings.