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. You may add an addendum, up to one
page, that describes the political difficulties in taking your analysis
seriously.
The assignment asks you to
analyze the knowledge claims in a policy (hence the focus on cause/effect
claims, ethical claims, etc.). The
groups that are for and against a policy may take those positions for other
reasons. Knowledge claims in a
policy are instrumental: Can we do
this? Do we know how? Will the policy produce the intended
effects? Will it produce undesirable
effects? Why do we think the world
we seek to create is better than the one we inhabit?
An inventory of who is for and
who is against a policy, with quotes from each side, does not directly answer
these questions. To answer them
requires you do unpack the policy, list the knowledge claims you find
interesting, do some research into the existing state of knowledge, and reach
some conclusions about one or more of them.
The purpose of the addendum is
for you to describe, if you like, the political difficulties in taking the
previous pages seriously. There
are political reasons for avoiding knowledge.
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.[1] 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.[2] 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?[3]
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.[4]
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.[5] 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:[6]
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?”[7] 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?”[8] 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.[9] 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.[10] 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.[11] 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.[12]
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]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]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]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]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]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]Meehan,
Reasoned
Argument, p. 158.
[7]Eugene
J. Meehan, Ethics
for Policymaking: A Methodological Analysis (New York: Greenwood Press,
1990), p. 11.
[8]Meehan,
Ethics, p.
11.
[9]Standards
for arguments are discussed in Meehan, Ethics, pp. 118-9.
[10]Eugene
J. Meehan, Ethics.
[11]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]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.