Short Version:
For the purpose of this assignment, a policy is a rule applied in a specific situation that produces a specific change in some state of human affairs. The rule enacts, actually produces, a priority, the desired state of affairs. This means the policy contains some claims about cause and effect relationships (‘the rule will bring about the new state of affairs’), and about norms or values (‘the new state of affairs is better than the current one or other alternatives’). Policy analysis can focus on (a) the rule itself, (b) the ability of the rule to produce the desired state of affairs, and (c) the values embodied in the policy. For example, a rule might violate a civil right; it might bring about, in addition to the desired outcome, the deaths of innocent people; and it might pursue values that are not accepted by an overwhelming majority of citizens. It might cost too much for the benefits achieved. It might be the best we can do in all these respects. There is no magic technique with any of this—humans search for reasons to believe claims, and where possible test these claims. The usual rules about methodology apply.
For
your papers, choose a policy that is currently up for grabs in national government,
and apply this approach.
Long Version:
This approach to thinking about policy is described in more detail elsewhere. Here is one source….
[The following material appears, slightly revised, in print as part of THE MAKING OF TELECOMMUNICATIONS POLICY, by D.W.S. Olufs III, pp. 11-16. Copyright (c) 1999 by Lynne Rienner Publishers, Inc. Used with permission.]
In practice, the disciplines of political science and public administration do a poor job of approaching the question, What Policy Should Be Made? The question suggests that a particular policy be analyzed, and that calls for action in the field of policy analysis.
Sometimes policy analysis means the description of general directions in government spending. Is defense spending increasing or decreasing? Are the poor getting more or less under this administration? So construed, it is not clear what one means by a ‘policy.’ It is a trend in spending, but it might also be a law that creates an agency empowered to do many activities, or it might be a change in a specific rule, such as an exemption from cable television service price controls for cable systems serving less than 15,000 customers. A loose concept of policy defies analytical precision.
The field itself often focuses on program evaluation.[i] A program is a collection of activities, usually within one governmental agency but not necessarily so, directed toward some set of similar goals. This mutation of the idea of policy analysis is unfortunate. It is essentially a bureaucratic classification, based on the need of government agencies to evaluate and justify annual budgets. This apparent concession to practicality endorses an approach to knowledge that guarantees frustration, and leaves policy debate mainly in the hands of program advocates and detractors.
The distinction presents a challenge to an analytical perspective. A program is, in one sense, a collection of resources: money, legal authority, skilled people, buildings or offices, equipment, procedures, and the like. It is also a collection of outputs: procedures applied to cases produce changes in the world. In practice, program evaluation focuses on a wide range of attributes, such as efficiency measures (dollars per case), productivity measures (cases per worker), process or organizational measures (span of control, comparisons of case procedures), and benefit-cost analysis. Program analysis is not one thing--programs are complicated and analysis is required by many authorities, such as executive budget offices, legislative committees, and top managers. This sense of evaluation is a ‘field’ only because of academic departments and terminology within bureaucracies. There is no unifying approach to knowledge.
Even though political actors tend to sound sure of their claims, we should remain skeptical about cause and effect relationships. David Hume’s lesson on the problem of knowledge lays out the challenge for us. We assert from experience that x leads to y. We further assert that the future will resemble the past, so that future x’s will lead to more y’s. Yet this is a fallacy: The principle that we can learn from experience is not prior to experience, although we use it as if it is.
Hume suggested a practical solution. We get in the habit of considering x’s in relation to y’s, because we care about achieving y’s. We are not indifferent toward outcomes. He wrote that “reason is, and ought only to be the slave of the passions, and can never pretend to any other office than to serve and obey them.” A political discussion of our ends can be disciplined by analysis of experience with earlier attempts to achieve similar ends.
The knowledge problem can be illustrated through an analogy to policies made in the fields of agriculture and medicine.[ii] Knowledge is collected with clear goals in mind. A particular patient is ill, and the criterion for success is the patient’s health. A farmer is growing tomatoes, and the criterion for success is yield per acre at a given quality standard. In these situations the purpose for policymaking is clear, the farmer or physician focuses on an action taken to bring about a desirable change, and the action is evaluated in light of their purposes.
Is something like this possible in public policies? Can they be based on knowledge, as conceived here?[iii]
The farmer and the physician take action to produce a preferred outcome. They do applied science--taking into account the social situation, thus using both empirical and normative knowledge. What they are doing is complicated, but they use the same mental tools available to any healthy person.[iv]
First, they have their priorities. This means they have made conclusions about why they prefer one outcome to the other. Farmers and physicians generally have these imposed from the outside (a tomato sauce maker pays by the pound for a stated quality, so greater yields per acre is the best outcome; patients want to return to normal health). In the world of policy this is more difficult, but in principle is the same problem. What are the possible outcomes--that is, given the range of end states that are within our power to bring about, which do we prefer? Why? Once we have answered those questions, we can describe our priorities.
Second, the farmer and the physician have rules for action. The policy takes the form of a rule: In situation m, do y. The farmer knows enough about the state of his tomato field on a particular day so that his discovery of a certain insect elicits a response. The farmer has several options: spray with pesticides a, b, or c within a certain number of days; spray with bacillus h within a certain number of days; release predator bug n in certain numbers within a certain number of days; do nothing. Based on knowledge acquired from earlier personal experience and the acquired experience of others, the farmer arrives at a rule to apply in the specific situation, say, spray with bacillus h. The physician is similarly guided by knowledge of similar cases. A fifty year-old Caucasian male, former smoker but otherwise normal good health for his age, complains of a sore throat. There is some localized irritation below the left tonsil, and one lymph node on the left side is swollen. In a twenty year-old nonsmoking patient it is highly likely that the cause is a viral infection that will run its course in ten days. The physician would culture the irritated area to rule out a nasty strain of strep known to be in the area, but would otherwise advise the patient to check in again if it has not cleared up in ten days. The fifty year-old man presents a different story. A significant number of such cases are early tumors. While a $1,000 MRI scan (magnetic resonance imager) or a biopsy are too expensive or dangerous at this early stage, a more diligent watch is in order than for the twenty year-old. The action is different because experience with similar cases is different.
In the world of public policy this detailed and specific knowledge of cases is often difficult to acquire. This is not because the information is impossible to collect. It is usually because no one collected the relevant information and built experience that would inform an impending choice.[v] The lack of data is not surprising, given that policies often change for reasons unrelated to experience with actual cases. For examples, legislators and executives with broad goals acquire power and enact different visions about the proper role of government. The cuts or additions in various areas of the state or national budget are not based on detailed knowledge of cases. Farmers and physicians know they can’t act that way.
Third, the farmer and the physician are able to test their policies. The rule must force an outcome. That is, the rule must bring about the desired state of affairs, the priority, in the situation where it was applied. If it does not, the policy is a failure. If the farmer is not able to apply bacillus n to the field within the given number of days, the policy does not pass the test. If the physician has a bad tracking system, so that the fifty year-old patient feels a little better and ignores the frequent sore throats for six months--at which point an invasive cancer may have developed-- the policy does not pass the test.
The entire procedure of using this view of policy is described by Meehan:[vi]
Reasoned choice involves five basic stages or processes: (1) projection of a set of two or more outcomes on the future, using some selection of normative variables; (2) comparison of those outcomes, seeking reasons for preferring one to the others; (3) generalizing the preferred solution in that case to create a priority system; (4) application of the priority system to specific cases through appropriate policies; and (5) refining the structure in the light of experience with use.
The analytical approach involves three kinds of claims. Empirical claims answer questions of the type, “does evidence suggest the change to be introduced into the situation is likely to produce the desired outcome?”[vii] These kinds of claims are inherently testable, given the focus on outcomes on individual lives. For example, a policymakers might claim that “allowing telephone and cable television companies to enter each others’ businesses will reduce consumer prices.” Is this true? For which customers? How soon? By specifying the conditions under which the claim will be tested for identifiable individuals, all that remains is collecting facts. Normative claims answer questions of the type, “can reasons be found in our experience for maintaining that preference or priority?”[viii] These can’t be tested in the same way as empirical claims, but must instead rely on arguments. There is no magic for generating consensus on priorities, although a focus on policies narrows the range of arguments that need to be considered.[ix] For example, a policymaker might claim “we want the lowest possible prices for consumers.” The question follows, Why? Average prices insufficiently clarify the effects on specific individuals, so the claim should be bolstered by arguments about different classes of customers (businesses and households, poor and well-off customers, urban and rural, basic service and high-end customers, etc..) The normative claims may be less precise, but they only need to be specific enough to assert that one outcome is preferable to another.[x] Methodological claims answer questions about whether the other types of claims are appropriately drawn.
[Figure illustrating the model omitted]
This approach leaves many grounds for criticizing policy. First, and perhaps most important, is the effects a policy has on humans. Individual human beings are the bearers of the costs and benefits of government action. Vigorous argument is possible over what constitutes an improvement in the lives of people affected by a policy, and over which improvements or costs are most important to emphasize.
Criticism of a policy involves comparison with some other policy. That is, if one disagrees with a rule, one proposes another rule to be applied in the same situation. The argument focuses upon reasons for desiring the outcomes of one rule as opposed to the other.
This view of policy is a tough standard in that actual policymaking often fails to apply important parts of the procedure. It can be helpful to have an approach that sets benchmarks for learning from experience and clarifying both empirical and normative issues in policymaking.
The practical difficulties of applying this approach to policy are formidable. To begin with, priorities are the result of consensus on the nature of a good life. Our mainstream values, not to mention those of citizens who criticize the mainstream, are a collection of widely disparate propositions that fit together loosely.[xi] In our policymaking institutions the people who actually make important decisions are not the people with experience about relevant cases. The reasons for changes in legislation are typically quite broad--election campaign promises, a felt need to do something in the face of catastrophic events, compromise among contending interests, responses to broad social trends, and so on.[xii]
In practice, legislation is vague about desired outcomes. A preference for more competition in telecommunications, for example, is not terribly helpful in actual choice situations. A wide range of policies may be consistent with the command ‘to encourage competition.’ Resorting to the hearings record is unlikely to clarify the intent of Congress in such situations. Members of Congress may want to ‘lower prices for consumers’ or ‘create millions of new jobs’ and pass legislation in the belief that a general change in rules will accomplish these ends. The analytical approach instructs us to ask whether supporters of a policy have any reasonable basis for their claims.
The model does not ask about the intelligence or motivations of policymakers. Rather, given the conditions for basing policy on knowledge, how do specific policies and the policy process measure up?
NOTES
1.
[1]Approaches
to policy and program analysis are described in E.S. Quade, Analysis for Public Decisions (New York:
North-Holland, 1982); Edith Stokey and Richard Zeckhauser, A Primer for Policy Analysis (New York: W. W. Norton, 1978); Alvin
W. Drake, et.al., eds, Analysis of Public
Systems (Cambridge: MIT Press, 1972); Walter Williams, et.al., Studying Implementation: Methodological and
Administrative Issues (Chatham, NJ: Chatham House, 1982).
2.
[1]The analogy
is suggested in Eugene J. Meehan, Reasoned
Argument in Social Science: Linking Research to Policy (Westport, Ct.:
Greenwood Press, 1981). A similar approach is taken in Duncan
MacRae, Jr., and James A. Wilde, Policy
Analysis for Public Decisions (Duxbury Press, 1979). Additional examples of applications are discussed
in Harry P. Hatry, Richard E. Winnie, and Donald M. Fisk, Practical Program Evaluation for State and Local Governments, 2nd.
ed. (Washington, D.C.: Urban Institute Press, 1981).
3.
[1]An original
discussion of the topic is Charles E. Lindblom and David K. Cohen, Usable Knowledge: Social Science and Social
Problem-Solving (New Haven: Yale University Press, 1979).
4.
[1]Many people
in social science hold the notion that empirical and normative questions (or,
as the distinction is sometimes made, ‘fact and value’) should be approached
differently. Yet the intellectual
apparatus for testing the two types of claims is similar. The fact that people disagree about desirable
ends does not in principle bar us from collecting knowledge about the outcomes
of pursuing one or another course of action.
A way to face the problem is to restrict normative claims to instances
where policies change the lives of actual persons. Qualify of life variables can be
systematically investigated. See, for
example, Gary King, Robert O. Keohane and Sidney Verba, Designing Social Inquiry: Scientific Inference in Qualitative Research
(Princeton: Princeton University Press, 1994).
5.
[1]A case that
illustrates this problem is Eugene J. Meehan, The Quality of Federal Policymaking: Programmed Disaster in Public
Housing (St. Louis: University of Missouri Press, 1979).
6.
[1]Meehan, Reasoned Argument, p. 158.
7.
[1]Eugene J.
Meehan, Ethics for Policymaking: A
Methodological Analysis (New York: Greenwood Press, 1990), p. 11.
8.
[1]Meehan, Ethics, p. 11.
9.
[1]Standards
for arguments are discussed in Meehan, Ethics,
pp. 118-9.
10. [1]Eugene J.
Meehan, Ethics.
11. [1]The loose
construction of values, so that they do not offer clear guides to choice in
actual situations, is not impossible to overcome. Eugene Bardarch incorporated an approach to
value analysis in his The Implementation
Game: What Happens after a Bill Becomes a Law (Cambridge: MIT Press, 1977),
especially in the appendix on writing implementation scenarios. An approach to coping with value ambiguity in
the enforcement of regulations is offered in Eugene Bardach and Robert A.
Kagan, Going By The
Book: The Problem of Regulatory Unreasonableness (Philadelphia:
Temple University Press, 1982). When a
society lacks consensus on values general guidelines are not likely to have
much meaning. An example of learning
limited lessons from cases and extending the lessons to classes of cases is
Ronald Dworkin, Life’s Dominion:An Argument about Abortion, Euthanasia, and Individual
Freedom (New York: Alfred A. Knopf, 1993).
12. [1]See the account
of the origins of the idea of the National and Community Service Trust Act of
1993 in Steven Waldman, The Bill: How
Legislation Really Becomes Law: A Case Study of The
National Service Bill (New York: Penguin Books, 1996), revised and updated
edition.
[i]Approaches
to policy and program analysis are described in E.S. Quade, Analysis for Public Decisions (New York:
North-Holland, 1982); Edith Stokey and Richard Zeckhauser, A Primer for Policy Analysis (New York: W. W. Norton, 1978); Alvin
W. Drake, et.al., eds, Analysis of Public
Systems (Cambridge: MIT Press, 1972); Walter Williams, et.al., Studying Implementation: Methodological and
Administrative Issues (Chatham, NJ: Chatham House, 1982).
[ii]The analogy
is suggested in Eugene J. Meehan, Reasoned
Argument in Social Science: Linking Research to Policy (Westport, Ct.:
Greenwood Press, 1981). A similar approach is taken in Duncan
MacRae, Jr., and James A. Wilde, Policy
Analysis for Public Decisions (Duxbury Press, 1979). Additional examples of applications are
discussed in Harry P. Hatry, Richard E. Winnie, and Donald M. Fisk, Practical Program Evaluation for State and
Local Governments, 2nd. ed. (Washington, D.C.: Urban
Institute Press, 1981).
[iii]An original
discussion of the topic is Charles E. Lindblom and David K. Cohen, Usable Knowledge: Social Science and Social
Problem-Solving (New Haven: Yale University Press, 1979).
[iv]Many people
in social science hold the notion that empirical and normative questions (or,
as the distinction is sometimes made, ‘fact and value’) should be approached
differently. Yet the intellectual
apparatus for testing the two types of claims is similar. The fact that people disagree about desirable
ends does not in principle bar us from collecting knowledge about the outcomes
of pursuing one or another course of action.
A way to face the problem is to restrict normative claims to instances
where policies change the lives of actual persons. Qualify of life variables can be
systematically investigated. See, for
example, Gary King, Robert O. Keohane and Sidney Verba, Designing Social Inquiry: Scientific Inference in Qualitative Research
(Princeton: Princeton University Press, 1994).
[v]A case that
illustrates this problem is Eugene J. Meehan, The Quality of Federal Policymaking: Programmed Disaster in Public
Housing (St. Louis: University of Missouri Press, 1979).
[vi]Meehan, Reasoned Argument, p. 158.
[vii]Eugene J.
Meehan, Ethics for Policymaking: A
Methodological Analysis (New York: Greenwood Press, 1990), p. 11.
[viii]Meehan, Ethics, p. 11.
[ix]Standards
for arguments are discussed in Meehan, Ethics,
pp. 118-9.
[x]Eugene J.
Meehan, Ethics.
[xi]The loose
construction of values, so that they do not offer clear guides to choice in
actual situations, is not impossible to overcome. Eugene Bardarch incorporated an approach to
value analysis in his The Implementation
Game: What Happens after a Bill Becomes a Law (Cambridge: MIT Press, 1977),
especially in the appendix on writing implementation scenarios. An approach to coping with value ambiguity in
the enforcement of regulations is offered in Eugene Bardach and Robert A.
Kagan, Going By The
Book: The Problem of Regulatory Unreasonableness (Philadelphia:
Temple University Press, 1982). When a
society lacks consensus on values general guidelines are not likely to have
much meaning. An example of learning
limited lessons from cases and extending the lessons to classes of cases is
Ronald Dworkin, Life’s Dominion:An Argument about Abortion, Euthanasia, and Individual
Freedom (New York: Alfred A. Knopf, 1993).
[xii]See the
account of the origins of the idea of the National and Community Service Trust
Act of 1993 in Steven Waldman, The Bill:
How Legislation Really Becomes Law: A Case Study of The
National Service Bill (New York: Penguin Books, 1996), revised and updated
edition.