Policy analysts' roles and value orientations: An empirical investigation using Q methodology

Policy Analysts‘ Roles and Value Orientations: An Empirical Investigation Using Q Methodology

Dan Durning Will Osuna

Abstract Several scholars have suggested that policy analysts and policy researchers can be classified as falling into one of a small number of ideal types. These ideal-type models are based largely on analysts’ views of their roles in an organization and their value orientations, including their relationships with clients, their perceptions of their responsibility to the public, and their acceptance of professional norms. To determine to what extent practicing policy analysts and researchers resemble the ideal types, we administered Q-sorts to 38 analysts and researchers in three states. I n our analysis o f the Q-sorts, we identified five types. Also, we found that the analysts and researchers hold in common many views of analytic roles and values.

INTRODUCTION AND OVERVIEW

Policy analysts and researchers work in a variety of government agencies that make public policy decisions, and in private and nonprofit organizations that seek to influence those decisions. The distribution of such employees across diverse settings raises some interesting questions-so far only partially explored-about what their work has in common and how their roles and value orientations compare.

Aside from Arnold Meltsner’s [ 19761 pioneering look at policy analysts in the bureaucracy, research on the work, roles, and values of policy analysts has not used formal empirical methods. Instead, researchers on the topic, such as Jenkins-Smith [1982], Torgerson [19861, and Jennings [1987a], have formulated ideal-type models of the way that analysts and researchers approach their jobs, but have not systematically tested the validity of the models.

This article presents research that takes a step toward identifying how practicing policy analysts and researchers view their roles in organizations and society, and how they weigh the competing pressures on them from their clients, their profession, and their personal definitions of public good. The research explores these questions:

Journal of Policy Analysis and Management, Vol. 13, No. 4, 629-657 (1994) 0 1994 b the Association for Public Policy Analysis and Management Publishediby John Wiley & Sons, Inc. CCC 0276-87391941040629-29

630 PoIicy Analysts’ Roles and Value Orientations

1 . To what extent do policy analysts and researchers resemble the ideal types suggested by the scholars who have written on this topic?

2. If the ideal-type models do not describe policy analysts and researchers well, what different types of policy analysts exist, what do these different types have in common, and how do they differ most?

3. Which of the following factors seem strongly associated with those differences: professional backgrounds, organizational contexts, or other char- acteris tics?

In the first section of this article, we summarize the key ideas in research on the roles and value orientations of policy analysts. We then describe our research approach, discussing the rationale for using Q methodology, how the Q sort was constructed, and how the P sample was chosen. Finally, we describe the results of the Q sorts and explain our findings.

CLASSIFYING POLICY ANALYSTS AND RESEARCHERS

A discussion of types of policy analysts and policy researchers should begin with definitions, because these job titles may create confusion about who and what is being studied. That lesson was learned when we asked various people-mostly managers of state and local government agencies-to recommend policy analysts and researchers to participate in this study. Many were unsure exactly what such jobs entail. Several said they did not know of anyone who does policy analysis. Others seemed to think of those positions only in terms of researchers with doctorates. And still others had a more expansive view, suggesting, among others, government lawyers providing legal analysis.

Our definitions of policy analysts and policy researchers are adopted from Weimer and Vining [1992], who define policy analysis simply as “client- oriented advice relative to public decisions and informed by social values” (p. 1). Accepting that definition, we define policy analysts as the people who transform data, information, and other analytic inputs into policy advice (or enlightening information) relevant to a particular decision for a specific client.’

Like policy analysts, policy researchers also transform analytic inputs into policy advice or information relevant to a decision. However, they differ from analysts in their organizational location, relationship to clients, the sophistication of methods they use, and the time frame of their work.2

0 Policy researchers often conduct research for organizations other than the one in which they work, or their research may be intended for no particular client, but to inform whomever is interested. Analysts are more likely to be members of the same organization as their clients.

0 Researchers are more likely than analysts to use sophisticated quantita-

’ Hank Jenkins-Smith [1982, p. 881 defines a policy analyst as “one who uses the systematic analysis of public issues to provide a client, a policymaker, with advice.” * Weimer and Vining [1992, p. 41 succinctly differentiate policy analysts and policy researchers in a summary chart. Cook and Vaupel [1985] describe three “research styles,” showing the differences in policy analysis, policy research, and applied social science research.

Policy Analysts’ Roles and Value Orientations 1 63 1

tive methods to investigate an issue. Analysts are more likely than researchers to draw mainly on secondary sources and qualitative methods. Researchers tend to have longer time frames for their work. Analysts are more likely to have short-term projects with firm deadlines.

With such broad definitions of policy analysts and researchers, our question is whether analysts and researchers share some roles and value orientations, or whether these job titles convey little useful information about what job incumbents really do and how they perform their work. We wonder to what extent policy analysts and researchers have commonalities, and whether these are greater than their differences.

The roles and value orientations of policy analysts have been examined by a few researchers. The main formal empirical work was done by Arnold Meltsner in the early 1970s. He interviewed 116 analysts and researchers in the federal bureaucracy, finding that “analysts had a variety of orientations to their jobs” and “they placed different weights on what they do and how they do it” (p. 17). He summarized his findings as follows:

Policy analysts are a highly variegated species . . . Even if we could hold . . . various situational and background factors constant, policy analysts would still differ. They come to their jobs with different incentives. They have different internalized standards of accomplishment and success, and even those with a common education rely on different skiils and strengths in the performance of their tasks. Moreover, they have different views about policy analysis and its impact on policymaking. (p. 14)

In his book, Meltsner classifies policy analysts as “technicians,” “politicians,” and “entrepreneurs,” differentiating among them on the basis of their technical analytic skills and political skills. Of the three ideal types, Meltsner clearly prefers entrepreneurial analysts, who combine technical and political skills.

Behn [1981] differentiates between two ideal types who participate in the “game of public policy”: policy analysts and policy politicians. The policy analysts are similar to Meltsner’s technicians; they are concerned with economic efficiency and how policies affect society. The policy politicians, similar to Meltsner’s politicians, are described as being most concerned with distribu- tional issues and how policy affects individuals and groups. The result is a competition of economic rationality and political rationality [Behn, 1981, p. 20 11. Like Meltsner, Behn prefers that analysts combine both technical and political skills, suggesting that:

The analyst’s responsibility extends beyond the mere passive determination of political feasibility to the active creation of a political strategy. The complete policy analyst will not only recommend the best policy alternative but also the best political strategy with which the client can win the adoption and implementation of this alternative. (P. 222)

Both Jenkins-Smith [ 1982, 19901 and Weimer and Vining [ 19921 speculate that analysts fall into categories that differ somewhat from those suggested by Meltsner. Jenkins-Smith maintains that analysts’ roles are shaped by their work context, including such things as the client-analyst relationship (the client’s influence on the analyst’s career, and the proximity oi the analyst to the client) and the nature of the policy arena in which the client functions (the

632 Policy Analysts’ Roles and Value Orientations

client’s commitment to particular policy issues; levels of analytic tractability; and the analyst’s understanding of the predominant mode of analysis).

Jenkins-Smith describes three models of analysis. The first is the objective technician as depicted by Meltsner and Behn. These analysts “desire to remain aloof from politics.” They “want to be insulated from the internal games of influence and policy disputes . . . to be set free to develop ‘the best program’ in the hopes of having it selected on the basis of its objective merits” [1982, p. 921.

The other two types of analysts are advocates who are “political actors” [Jenkins-Smith, 1982, p. 931. One is an “issue advocate” who fights for efficiency (like Behn’s complete policy analyst), or perhaps another value such as equality, fiscal restraint, freedom, or human dignity. These analysts seek opportunities to shape policies in a specific direction they believe correct. According to Jenkins-Smith, “Analysts championing a particular cause or social interest, such as advocates for the poor, may fit this conception best” (p. 93). The second political actor is a “client’s advocate” who promotes the policy positions preferred by his or her client (p. 95). Neither of these types favor providing objective, value-neutral advice over the opportunity to contribute persuasive advice able to influence policy decisionmaking.

Weimer and Vining [1992] adopted the three Jenkins-Smith types, suggesting that they are “conceptions of the appropriate role of the analyst” (p. 17). These authors maintain that each role gives priority to one of three key values that influence the work of analysts: (1) analytic integrity (objective technicians); (2) responsibility to the client (client’s advocate); and (3) adher- ence to one’s concept of good (issue advocate). They also suggest that competition between these roles and associated values creates ethical dilemmas for some policy analysts.

Another set of literature examines the ideal-type analytic roles more criti- cally, then offers an alternative or emergent type of policy analyst. Jennings [1987a] maintains that there are two approaches to policy analysis. The first is “policy analysis as science” conducted by analysts and researchers who embrace positivism, objectivity, and value neutrality. The second is “policy analysis as advocacy” conducted by analysts and researchers who reject objectivity and value neutrality, and who view themselves, similar to lawyers in the legal system, as playing a role in an adversarial system of policymaking. Thus, while “scientists” try to produce objective knowledge, the advocates trade in persuasive subjective opinion. Jennings [1987a, p. 1271 asserts that “analysts try to act like scientists when they can, arid as advocates when they must.”

After critiquing the failings of both models, Jennings proposes a third approach, “analysis as c o ~ n s e l . ” ~ The analyst-counselor, according to this model, functions as a participant-observer, an interpretative analyst who would help interpret political and social reality “in service of change.” The analyst would “strive to fashion an interpretation of what the public interest requires that can survive a collective process of rational assessment and deliberation” [Jennings, 1987b, p. 1471. This third model is Jennings’s view

The positivist foundations of analysts as scientists or technicians have been criticized for decades. See, for example, Tribe 119721, Innes [1990], Dryzek [1990], and Fischer [1990].

Policy Analysts’ Roles and Value Orientations 1 633

of what policy analysts would do in a more democratic society to contribute to “practical rationality” in deci~ionmaking.~

Torgerson [ 19861 also rejects the efficacy of the two “faces” of policy analysis he says are now at work. The first is the face of the Enlightenment, a positivist face with a technocratic orientation. It represents the victory of knowledge over politics. The second face is “the somber side of the Enlighten- ment vision.” This face is the unmasked domination of politics over knowledge. It reveals objective analysis as the tool of the powerful and policy analysts as “a mask for the surreptitious exercise of power” (p. 39). With this face of policy analysis, “political neutrality . . . can be grasped as an illusion which tends to suppress critical questions about the political context in which policy analysis is applied” (p. 38).

Like Jennings, Torgerson foresees a third face, “an emerging tendency,” that will transcend the problems of the first two faces. The third face adopts postpositivist analysis that “returns the analyst to this world as an active participant” (p. 40). According to Torgerson, these interpretative analyses will help reason work in a participatory democracy.

THE RESEARCH DESIGN: USING Q-METHODOLOGY

In the introduction, we identified threc questions that we intend to address with our research: (1) To what extent do policy analysts and researchers resemble the ideal types suggested by the scholars who have written on this topic? (2) If the ideal-type models do not describe policy analysts and researchers well, what different types of policy analysts exist, what do these different types have in common, and how do they most differ? and (3) What factors seem most strongly associated with those differences: professional backgrounds, organizational contexts, or other characteristics? To explore those questions, we use the Q-technique, an intensive methodology that per- mits researchers to map the attitudes of a set of respondents toward some issue under study.

Q-Methodology History, Applications, and Rationale

Q methodology is now nearly 60 years old, dating from its originator’s first application [Stephenson, 1935a, 1935bI. Since that original contribution, more than 2000 papers using Q have been published [Peritore, 1990, p. 111. Q has been used in a broad range of fields, most relevantly for studies in psychology, sociology, social psychology, political psychology, and political science.

We chose Q-methodology because it provides procedures for the empirical study of human subjectivity. Q is also relatively inexpensive, very portable, and often highly conducive to interviewing participants. During the field administration, or Q-sort, participants demonstrate how they think and feel about a group of stimuli statements. The participant is presented with a Q- sample consisting of printed statements. How participants sort these statements along a continuum of valences ranging from extreme disagreement to

See Torgerson [1986], Dryzek [1989, 19901, and Fischer [1990] for additional discussion of how a new type of policy analysis (and policy analysts) would contribute to a “participatory democracy” based on a different type of rationality.

634 1 Policy Analysts’ Roles and Value Orientations

extreme agreement communicates their “operant subjectivity” at the time of the administration. Brown [1980, pp. 5-61 summarizes Q-methodology as follows:

Simply stated, Q technique is a set of procedures whereby a sample of objects is placed in significant order with respect to a single person. In its most typical form, the sample involves statements of opinion (Q sample) that an individual rank-orders in terms of some conditions of instruction-e.g., from “most agree” ( + 5 ) to “most disagree”(-5). The items so arrayed comprise what is called a Q sort. Q sorts obtained from several persons are normally correlated and factor-analyzed by any of the avail- able statistical methods. Factors indicate clusters of persons who have ranked the statements in essentially the same fashion. Explanation of factors is advanced in terms of commonly shared attitudes or perspectives. Q methodology is the body of theory and principles that guides the application of technique, method, and explanation.

Readers not well acquainted with Q-methodology should consult Brown [1980] or McKeown and Thomas L19881 for an overview of this technique, its advantages and disadvantages’ For arguments concerning the value of Q-methodology in policy-related research, see Dryzek [ 19901.

The Q-Sample

In Q-methodology, the Q-sample consists of statements (verbal stimuli) drawn from a parent population. For our study, the population was made up of statements by researchers (and policy analysts as quoted by researchers) about the possible roles and value orientations of policy analysts.6 We collected as many of the population statements as possible from a variety of sources, including Meltsner [ 19761, Jenkins-Smith [ 19821, Weimer and Vining [1992], Majone [1989], Behn [1981], Jennings [1987], Amy [1984], Torgerson [1986], Tullock [1965], Lynn [1987], and Heineman, Bluhn, Peterson, and Kearney [1990]. From these sources, we gathered a total of 118 statements?

An excellent source of information about Q-methodology is the Q-METHOD e-mail list set up by Steven Brown at Kent State University. Through the Q-METHOD list, researchers can obtain QMETHOD, mainframe software that performs the analysis of Q-sorts, identifying the factors and presenting information needed to interpret them. The QMETHOD software was used for the analysis described in this study. 6Brown [1980, p. 1731 writes, “the term ‘population’ refers to the corpus of verbiage uttered vis-a-vis the subject matter under investigation. . . . The term ’sample,’ then, refers to a subset of the stimulus population.” Elsewhere, Brown writes about the “flow of communicability surrounding any topic” as a concourse. From this concourse, a sample of statements is drawn for the administration of the Q-sort. (This discussion of Q-samples was part of ane-mail “tutorial” on Q-methodology written by Stephen Brown and sent to the QUALS-L@UCA [qualitative research] e-mail list. This tutorial came in eight parts, beginning in December 1991 and continu- ing into January 1992. Instructions for receiving the tutorial can be obtained by subscribing to the Q-METHOD e-mail list.)

The concourse consists of discourse about how policy analysts and researchers view their jobs, including the roles they play in the policy process and the values that affect thcir work. The statements were taken from articles and books on these topics, and they include quotations from analysts and researchers and representations of the views and opinions of different types of analysts as understood by researchers addressing these topics. Most of the statements have been formulated by researchers who are attempting to explain the attitudes and opinions of different “ideal-type” analysts.


Table 1. Framework for Q-statement population sample.

Types of Analysts A. Objective technician B. Client’s advocate C . Issue advocate Dimensions of Analysts’ Roles and Value Orientations Perceptions of 1. main responsibilities and purpose of policy analysts and analysis 2 . to whom analysts are primarily responsible (and source of legitimacy for

3. the proper activities of analysts and approach to analysis 4. definitions of analytic success, failure, and quality 5. the context of analysis and policymaking

analysts)

To construct a Q-sort with a representative sample of statements, we formulated an inductive factorial design for the classification of the statements [see McKeown and Thomas, 1988, pp. 28-29]. The design is shown in Table 1. It consists of two dimensions (types of analysts and dimensions of analysts’ roles and value orientations), a total of 15 cells. This factorial design was constructed so that the statements selected for the Q-sort would represent, to the best of our judgment, the diversity of expressed propositions about policy analysts’ roles and value orientations.

As the statements about policy analysts’ roles and value orientations were collected, they were assigned to one of the categories in the factorial design. After all of the statements were assembled, the selection of statements to represent the different categories was guided by these criteria: (1) the stimuli statements were to express the fullest possible range of cell characteristics (i.e., we sought to maximize the diversity of the stimuli statements representing each cell); and (2) stimuli statements had to be readily understandable.

In assigning statements to the categories, we found that several statements represented the views of both categories B (client’s advocate) and C (issue advocate). Thus, as shown in Table 2, some statements were used to sample the combined views of type B and C analysts.

For some cells, the number of statements was large, and we had to select carefully those that expressed the full range of the characteristics of the cell. For other cells, the list of statements was short and selecting statements was simple. Because of the larger number of statements in dimensions 1, 3, and

Table 2. Distribution of Q-sample.

A B C B/C Total

1 3 3 3 0 9 2 2 2 2 0 6 3 3 2 2 2 9 4 2 1 1 2 6 5 3 1 0 5 9 Total 13 9 8 9 39


5, we used a sample of three statements to capture the full diversity of those views. For dimensions 2 and 4, two statements were adequate.’

Our Q sample consisted of 39 statements to be sorted by participants along the following continuum:

Score -4 -3 -2 -1 0 + l +2 +3 +4 Number of statements 2 3 5 6 7 6 5 3 2

The Q-statements are shown by number (randomly assigned) in Appendix A. Following each statement is the cell it represents and the weighted average sort score for each of the five factors that were identified (as descibed below), starting with factor A and ending with factor E. In Appendix B, we show which statements represent each of the cells.

The Person ( P I Sample

Because the purpose of this research is to identify how policy analysts and researchers view their roles and value orientations, the person (P) sample includes practicing policy analysts and policy researchers. We sought a diverse group of analysts and researchers working in state or local governments (or university-based researchers who address state or local issues). This diversity was obtained by administering the Q-sorts to analysts and researchers in Arkansas, California, and Georgia. Furthermore, we included analysts and researchers working in state government agencies, special districts, local government departments, local government executive offices, advocacy organizations, and university research units.

We included in the P sample some respondents with similar characteristics. Thus, most of the California respondents are graduates of the same public policy school; the Arkansas respondents work at the same university-based institute of government; and several of the Georgia respondents are university-based policy researchers. Including these groups with common educational experiences or workplaces allowed us to explore to what extent the characteristics they have in common are reflected in how they approach their jobs as analysts and researchers.

The total P sample was 38.’ Of those, 9 have MPPs from the Graduate School of Public Policy at the University of California, Berkeley; 7 are policy researchers at the Vinson Institute of Government, University of Georgia;

* One reviewer expressed unease about varying the number of statements representing each cell. The fear was that selecting a different number of statements for different cells would negate one of the purposes of factorial design: to control researcher bias in selecting particular kinds of statements.

We think using different numbers of statements for different cells was justified because it helped us construct a Q-sample that represented the diversity of statements better than the alternative of having the same number of statements for each cell. A close reading of Brown [1980] reveals no injunctions against this type of sampling. In fact, the use of factorial design is not even a requirement of Q-methodology. Brown [1980, p. 1861 notes that the selection of statements is “more a n art than a science.” but there are scientific principles that can be called upon for guidance. We believe that we followed those scientific principles and that our decision to use differential cell sampling enabled us to achieve the goal, as described by Brown [1980, p. 1891, “to produce a sample of stimuli more nearly approximating the complexity of the phenomenon under investigation.”

Because two people (with similar jobs in the same organization) collaborated on one of the Q-sorts, a total of 38 people participated in the study producing 37 Q-sorts.


and 4 are researchers or analysts at the Arkansas Institute of Government, University of Arkansas at Little Rock. Aside from 4 other respondents who have advanced degrees from the University of Georgia, the remaining respondents share no organizational or educational affiliations.

This P sample includes 7 people working in local government agencies or authorities, 12 in state government agencies, 4 in nonprofit advocacy groups, 1 in a regional authority, and 13 in public universities. Of the 38 participants, 14 are female and 24 male. Their ages range from 26 to 55. Of the respondents, only two are racial minorities, one an African American and the other an Asian American.

Administering the Q-Sorts We administered the Q-sorts a t the place of business (or, in one case, at the home) of each respondent, giving instructions on how to complete the sort and answering any questions about it. Before administering the Q-sorts, we briefly interviewed the respondents about what their jobs entail, the methods of their work, and their clients. After the sort was completed, we often asked the respondent to give his or her reaction to the sort or to explain why he or she assigned certain statements to the -4 and +4 categories. Also we collected information on the respondent’s age, educational background, and previous experience in policy analysis.

Following the usual Q-methodology, we correlated the sorts of all respondents, creating a 37 by 37 matrix. This matrix was factor analyzed using the principal components method, though the usual data locations were changed so that the respondents were the variables and the sorts were the observations. We used varimax rotation and, after examining the initial results, concluded that five factors could clearly be identified and explained.’O We judged that the additional factors met neither normal statistical nor judgmental criteria for their acceptance as meaningful separate factors. Of the 37 respondents, 18 clustered in Factor A, 12 in Factor B, 10 in Factor C, 3 in Factor D, and 3 in Factor E. Ten respondents loaded on more than one factor, and 3

l o In earlier stages of our research, we tested other types of objective rotation, including promax, and identified either identical or very similar factors.

A reviewer suggested that judgmental factor rotation should have been used rather than an objective method like varimax. This suggestion reflects Brown’s advocacy of judgmental rotation. He wrote [1980, p. 331, “It is often worthwhile to rotate factors judgmentally in keeping with theoretical, as opposed to mathematical criteria.” Such judgmental rotation is easy to carry out with the QMETHOD software.

In practice, this exhortation for judgmental rotation has often been ignored by researchers, including Brown, who have published articles using Q-methodology. For example, Dryzek [ 19931, Goldman [1991], Ascher [1986], Coke and Brown [19761, and Brown and Ellithorp [1970] used objective methods of rotation, usually varimax. In fact, of all the Q-based research that we reviewed, only Thomas and Baas [1991] reported the use of judgmental factor rotation. Our review of Q-based social science research led us to agree with this statement by Brown in an e-mail message to the QTEMP list on January 25, 1992:

[Judgmental rotation] is obviously a topic that requires more attention on our part as theoretical rotation was something that Stephenson did routinely and that most of us do not do, probably because we lack conviction as to its efficacy and legitimacy.

We did try judgmental rotation, but had no confidence in the results because we felt that we had no strong theoretical bases to guide our factor rotation. Also, the process of manually rotating so many pairs of factors left us uncertain about the results. Thus, we have followed in our research the pattern of reporting and using the results of the objective factor rotation.


respondents did not load significantly on any factor. See Table 3 for the factor scores and characteristics of the respondents.

Factor coefficients above 0.41 were accepted as statistically significant at the 0.01 level. This cutoff value was calculated as 2.58 times the standard error (SE) for the factor loadings. The SE was calculated as 1 divided by the square root of the number of items in the Q-sample [see McKeown and Thomas, 1988, p. 501.

FINDINGS: DESCRIBING THE TYPES OF POLICY ANALYSTS

Each of the five factors shown in Table 3 represents a type of policy analyst with role and value orientations that differ in some ways from those of the other types. These different views can be discerned: ( 1 ) by identifying the statements with which each type of analyst agreed or disagreed the most (the statements assigned +4, -4, + 3 , or -3 scores); and (2) by identifying the Q-statements for which the scores differ most. It is also possible to determine what role and value orientations the analysts have in common by identifying the statements that they sorted similarly, assigning the same or nearly the same score.

The weighted average rank-scores for each statement are shown in Appen- dix A. Our analysis of the Q-statement scores for each of the five factors-types of analysts-shows that each resembles in some ways one of the three “ideal type” analysts described by Jenkins-Smith and other researchers, but that their attitudes are less consistent and more complex than the ideal types. The analysts share many views, as shown in the positive correlations of the factors (see Table 4). And some of the factors are highly correlated.

The main differences in Q-statement rank scores are on the statements related to these issues:

0 the view that analysts should provide objective, value-neutral advice. 0 the extent to which analysts participate in politics. 0 the extent to which personal opinions about policies should influence

the extent of an analyst’s responsibility to promote the interest of clients. 0 the willingness to shade policy analysis to promote a preferred policy.

analysis.

We summarize in Table 5 the views of each of the five types of policy analysts on these issues. In the sections that Follow, we discuss these issues and the types of analysts in more detail.

Factor A Analysts: Objective Technicians

Factor A analysts view their professional responsibility to be providing objective advice about the consequences of proposed policies (see scores on statements 33, 37, and 38). They are not inclined to be actively involved in the politics of policymaking, and they prefer to remain uninvolved in internal influence games and agency disputes (statements 2 and 35). Nevertheless, they agree that they have a responsibility to help formulate political strategies for their recommended policies (statement 25). And of the five types of analysts, they are the most concerned with analytic integrity rather than the


outcomes of policies they analyze or their responsibility to their clients (statements 5 and 17). They reject the idea of shading analysis to favor either their own or their client’s policy preferences (statement 1). Also, they do not believe they should promote their views, or those of their clients, in their policy analysis or research. Instead, they strongly agree that it is their responsibility to enable policymakers to “look in different ways at the nature of the social problems they have to address” (statement 21) and that they contribute to the “good society” by providing unbiased information to decisionmakers (statement 37).

The factor A analysts closely resemble Meltsner’s technicians, Behn’s policy analysts, and Jenkins-Smith’s objective technicians. However, as discussed later, they are not the blind positivists of Jennings [1987a] and Torgerson [ 1 9861.

The statement scores that best define these “objective technicians” and differentiate them from the other types of analysts are the following:”

0 Factor A analysts think that objectivity and value neutrality are important.

Statement 33: The proper role for the analyst is to provide objective advice about thc consequences of proposed policies. +4 +4 0 +4 +2 Statement 38: Analysts should strive to be objective and value-neutral. They should not let personal values or preferences affect their analysis of facts. + 3 +2 -2 0 -1

Statement 37: An analyst contributes to the good society, at least in the long run, by consistently providing unbiased advice even when it does not lead to the selection of personally favored policies. +3 +3 0 0 1 2

0 Unlike other analysts, objective technicians prefer to be free from politics; however, they agree with other analysts that they have a responsibility to provide advice on the politics of a preferred proposed policy. Statement 35: I prefer to be free from politics so that I can develop the best program alternative that, I hope, will be selected on the basis of its objective merit. + 2 0 -2 0 - 3 Statement 2: Politics is somebody else’s business. My main business is research, which is linked to policymaking. 0 -3 -4 -3 - 3

Statement 25: The complete policy analyst will not only recommend the best policy alternative but also the best political strategy with which the client can win the adoption and implementation of this alternative. +2 +4 +4 -1-4 +4 Factor A analysts are more concerned than other types of analysts (except,

I ’ The scores for each statement are reported, from left to right, from factor A to factor E.

Tab

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442 / Policy Analysts’ Roles and Value Orientations

Table 4. Correlations of the Q-factors.

Factor

Factor A B C D E

A 1 0.69 0.32 0.40 0.39 B 1 0.41 0.38 0.51 C 1 0.65 0.51 D 0.38 E 1

Note: The factor C responses are adjusted to reflect that all defining respondents had negative coefficients. Thus, the original correlations of factor 3 with other factors were negative values.

perhaps, factor B analysts) with analytic integrity rather policy outcomes and client interests. Statement 5 : I am more concerned with the outcomes of policies I analyze rather than things like analytical integrity and responsibility to the client. -4 -4 -2 + 2 -3

Statement 17: If it makes an impact it is successful, even if it is bad analysis technically. -4 -2 -1 -1 - 1

Statement 1 : When I am doing a policy analysis of a complex issue and the facts do not clearly favor the alternative I think is correct, I may shade the analysis in favor of my preferred outcome if that does not undermine the analytic plausibility of the analysis. -3 -3 -1 + 1 -2

Factor B Analysts: Client Counselors

These analysts share many of the values and views of the objective technicians, but see themselves more than the factor A analysts as agents of their clients. Although they mildly agree that their legitimacy in policymaking originates with their clients (see scores on statement 19) and that their success depends on producing analysis that reflects their client’s interests (statement 20), they are willing to go only so far to help clients get the policies they want. Thus, the client counselors are not as zealous in promoting their client’s interests as Jenkins-Smith’s client advocates, and they are more inclined to produce “objective” advice than advice that favors their clients’ interests.

Like objective technicians, the client counselors believe strongly that the proper role for an analyst is to provide objective advice (statements 33,37, and 38). Also, they share the values of objective technicians concerning analytic integrity (statements 1 , 5 , and 17). However, unlike factor A analysts, the client counselors see politics as part of their job (statements 2 and 25).

Factor B analysts seem tugged in one direction by their responsibilities to clients and in another by their preference for objective advice and inclination

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toward value neutrality. They strongly disagree with the statement that clients are “necessary evils” (statement 4). They agree that analysts will fail if the “come up with analysis that continually” reflects personal interests and not those of the client (statement 20) and that they must subordinate their own policy preferences when working for a client (statement 30). However, they reject the idea of shading analysis for the benefit of their clients (statement 28).

The client counselors agree with objective technicians that they have a responsibility to enable policymakers to look at social problems from different perspectives (statement 2 1). But unlike the objective technicians, they view their roles as producers of policy arguments (statement 24). Neither factor A or B analysts view themselves as advocates for their own preferences or for those of their clients; instead, they want their arguments to be based on objective research and analysis. Like factor E analysts, but unlike all others, factor B analysts agree that their objective advice and arguments can help achieve justice through “an adversarial process of give and take among advocates representing particular social issues” (statement 19).

The unique views of these analysts can also be seen in the discussions of Q-statement scores for factor A analysts, and the scores on the following Q- statements:

0 Factor B analysts view clients as their source of legitimacy and as the focus of their work.

Statement 14: Analysts derive their legitimacy as participants in the formation of public policy from their clients, who hold elected or appointed office or who represent organized political interests. 0 +1 0 -1 +1

Statement 20: If you come up with analysis that continually reflects your interests and not your client’s, you will fail. 0 c2 0 -1 +2 Statement 4: For policy analysts like me, clients are necessary evils. They provide the resources that allow me to work on interesting questions, but often they try to interfere with objective analysis. -1 -4 -3 -1 +1

Statement 30: I must relegate my policy preferences to a secondary position once I make a commitment to go to work for a client. +1 +2 -2 -4 -1

Factor B analysts agree that their job is to provide policy arguments as part of an adversarial process that can produce justice.

Statement 24: The policy analyst is a producer of policy arguments, more similar to a lawyer than to an engineer or a scientist. -1 +2 +1 + 3 0

Statement 19: Justice would be achieved through an adversarial process of give and take among advocates representing particular social interests. -1 + 1 0 -2 +2

0 Factor B analysts reject the idea of shading their analysis to favor their clients.

Policy Analysts’ Roles and Value Orientations 645

Statement 28: If an issue is very complex with no clear answer, I may shade my analysis in my client’s favor if doing so does not move the analysis beyond the pale of analytical plausibility. - 3 -2 0 +2 0

Factor C Analysts: Issue Activists

Factor C analysts12 are similar to the “issue advocates” described by Jenkins- Smith. They are neutral on the statement that the “proper role” for analysts is to provide objective advice (see scores above for statement 33 and 38), and they strongly reject value neutrality (see score for statement 9) and disagree with the idea that value decisions are best left to policymakers (statement 38). These analysts believe in personal involvement in the political aspects of policymaking (statements 2 and 25). For them, analysis is not an end; they are most interested in the outcomes of issues that concern them (statement 15). And they seek to steer policy in specific directions they think are best for society (see statement 3) , viewing themselves as advocates for ideas or causes in which they strongly believe (statement 27).

Despite being advocates, these issue activists reject (although not as strongly as factor A and B analysts) shading their analysis to favor preferred outcomes (statements 1 and 28). Also, they disagree with the statement that they are more concerned with outcomes than with analytical integrity and responsibility to their client (statement 5).

The characteristics of these “issue activists” can be seen in the statements discussed in the examination of the characteristics of factor A and B analysts and in the following statements:

0 Factor C analysts are more disposed toward personal activism in all aspects of the policy process to help get good policies enacted.

Statement 36: My job is not only to provide good advice, but to do good for society by helping get needed policies enacted. +2 +1 +4 + 3 +3

Statement 15: You are an intellectual eunuch if you don’t care if it’s not acted on. Analysis is not an end to itself. +1 0 + 3 + 1 - 1

Statement 27: I see myself as an advocate for an idea or an issue in which I believe very strongly. 0 -2 +2 +1 + 1

Statement 3: I am always looking for opportunities to shape policy in specific directions that I think are best. 0 -1 + 3 + l 0

0 Factor C analysts, like factor D and E analysts but unlike factor A and B analysts, do not believe their own policy preferences should be less important in their work than those of their clients.

’*Al l the respondents who significantly loaded on factor C had negative factor coefficients. To account for these negative loadings, all the respondent scores were recoded by multiplying them by -1. Thus, all positive scores became negative scores and negative scores become positive.


Statement 30: I must relegate my policy preferences to a secondary position once I make a commitment to go to work for a client. +1 +2 -2 -4 - 1

Statement 9: Value decisions are best left up to top policymakers and need not nor should not be the subject of policy analysis. -2 -1 -4 - 3 -3

0 Factor C analysts allow feelings for groups and ideas to affect their analysis.

Statement 3 1 : I care deeply about some problem or some group that is underrepresented in government, and that feeling affects my analysis. -1 - 1 +2 + I -4

Factor D Analysts: Ambivalent Issue Activists

The responses of the “ambivalent issue advocates” are highly correlated with those of the factor C issue activists, but also are moderately correlated with the objective technicians and client counselors. In combining these perspectives, the analysts appear to describe their actual roles as policy analysts as differing from the way they think policy analysis and research should really be done. These analysts strongly agree with objective technicians and client counselors that “the proper role for the analyst is to provide objective advice about the consequences of proposed policies” (see statement 33). However, they alone among the five types of analysts agree that they are more concerned with policy outcomes than with analytic integrity and responsibility to their client (statement 5). And they are also the only type of analysts that agree (though weakly) that, under some conditions, they would shade their analysis to favor a outcome they or their client prefers (statements 1 and 28).

This contradiction may partially be reconciled in the responses to statement 24, which show that these factor D analysts agree strongly that the policy analysts are producers of “policy arguments, more similar to a lawyer than to an engineer or scientist.” From this perspective, we can understand the factor D types as analysts who care about particular issues and view their job as bringing arguments about that issue into a policymaking arena-even though they might prefer to be providing objective advice.

Note that the factor D analysts appear to be more concerned about issues than the interests of client. They do not agree that “like attorneys, they should vigorously promote their clients’ interests” (statement 8). Also, they strongly disagree with the statements that their main job is to “provide the best possible case for my client’s preferred policy (statement 12) or that they should relegate their policy preferences to a secondary position once they make a commitment to go to work for a client (statement 30). However, they agree mildly with the statement that they are advocates for an idea or issue in which they strongly believe (statement 27), and they are looking for opportunities to shape policies in the direction they think best (statement 3 ) .

Is sum, these analysts seem pulled in two directions; one is the view that analysts should provide “objective advice,” and the other is that they


should act on their own strong opinions about issues. They end up on the side of promoting issues and show a willingness to go further than the factor C analysts in adapting their analysis to favor their preferred outcomes.

It should be noted that only three of the analysts who completed the Q-sorts loaded on this factor, and two of the three loaded significantly with higher factor scores on factor C. This small number of factor D analysts does not necessarily mean that they make up a small percentage of all analysts; our P sample was not a random sample of all analysts and researchers, so we have no knowledge of how the different types are spread throughout the total population of analysts and researchers. However, we can observe that all three of the factor D analysts have similar educational backgrounds (MPP degress from the University of California, Berkeley), and two of the three work in city management.

All the statements cited above as characterizing the factor D analysts have been presented in the discussion of the factor A, B, and C analysts, except for statements 8 and 12. These two statements were as follows:

Statement 8: Like physicians, analysts should “do no harm” to their clients; like attorneys, they should vigorously promote their clients’ interests. -3 -1 -1 -2 0

Statement 12: My main job as an analyst is to provide the best possible case for my client’s preferred policy alternative. -2 0 -1 -4 + 1

Factor E Analysts: Client Helpers

The factor E analysts have Q-sorts that are highly correlated with factors B and C . These correlations reflect that these “client helpers” are oriented toward assisting clients (like the client counselors), but are more inclined to be activists or advocates (like the issue activists).

These analysts seem to have some ambivalent feelings toward their clients. On one hand, they (alone among the different types of analysts) agree, though only weakly, that clients are necessary evils (scores on statement 4). (Note that the client counselors strongly disagree with this statement.) Also, they are unwilling to relegate their policy preferences to a secondary position once they go to work for a client (statement 30). However, they agree strongly that their “future lies in protecting [their] client’s future” (statement 10); also they agree, though mildly, with the statements that their main job as an analyst is to provide the best possible case for their client’s preferred policy alternative (statement 12), that policy analysis provides their client “with a strategy and ammunition” for a struggle between competing policy positions (statement 16), and that their legitimacy as participants in the policy formula- tion process comes from their clients (statement 14).

These analysts view themselves as strategists for their clients. They strongly agree that their job is to “map out and help implement a strategy for gaining acceptance” of the best program alternative (statement 29); that their job is not only to provide good advice, but “to do good for society by helping get needed policies enacted (statement 36); and that the complete analyst recommends “the best political strategy” for a client to win adoption of the best policy alternative (see statement 25). However, although viewing


themselves as strategists, the client helpers do not accept the idea of shading analysis (statements 1 and 28) or the primacy of outcomes over “analytic integrity and responsibility to the client” (statement 5). Also, they strongly disagree with the statements that they let deep feelings about some problem or group affect their analysis (statement 31), and that policy analysis is a “mask for the surreptitious exercise of power” (statement 22).

As with the factor D analysts, only three of the analysts in the P sample load significantly on this factor, and two of the three load significantly on another factor with a higher factor coefficient. One loads significantly on factor A and another on factor C . The person with the highest factor loading works in Georgia for an advocacy organization serving local governments. Another has spent several years in a management position for a Georgia county government. The third works for a state regulatory agency in Cali- fornia.

The statements cited above have been presented previously in conjunction with the discussion of the other factors, or are shown as follows:

Statement 10: I know that my future lies in protecting my client’s future. -2 0 -1 -2 + 3

Statement 29: Once I have figured out the best program alternative, my job is to map out and help implement a strategy for gaining acceptance of this policy choice. +2 + 1 +2 +2 +4

Statement 22: Policy analysis may look like escape from politics, but really is a mask for the surreptitous exercise of power. -1 0 + 1 0 -4

What the Different Types of Analysts Have in Common

In the preceding section, we identified five types of policy analysts and discussed how their values and their views of their roles differentiate them. In this section, we identify the values and views that these policy analysts and researchers have in common, as shown in their Q-sorts.

These common views are inconsistent with many of the criticisms of policy analysts as “scientists” who search for truth or the “right” answer to policy problems, and with assertions that technocratic policy analysts are oblivious to their politically charged environments. Although many analysts strive to perform objective analysis, few believe that they can find one best answer to a policy problem (statement 34).

This doubt about the existence of right answers does not mean that policy analysts and researchers are practicing postpositivists or interpretative analysts. The different types of analysts reject the statement that “any number can be leaned on” (statement 18), and there is little agreement with the statement that “the purported ethical and political neutrality of policy analysis is an illusion masking the inherently value-laden character of any analytic method” (statement 26). Most analysts view their work as a compromise between the ideal of analytic objectivity and the difficulty caused by the lack of one best solution for most problems and the need to promote the “best policy.”

According to these Q-sorts:

P o k y Analysts’ Roles and Value Orientations I 649

None of the five types of policy analysts believes that policy problems have one best solution (statement 34). They view themselves as working in a “pluralist policymaking system” with many competing actors (statement 23), and most types of analysts agree that they are producers of policy arguments, more like lawyers than scientists (statement 24).

Statement 34: Usually there is one best solution to a policy problem I analyze. -2 -4 -3 -3 -2

Statement 23: My work as a policy analyst fits into a pluralist policymaking system in which many competing actors have a part. +3 +3 +3 +3 +3

0 Despite the views about the lack of “one best solution,” analysts do not appear to view themselves as interpretative analysts. Most agree strongly that the proper role of the analyst is to provide “objective advice” (statement 33). They do not react strongly to idea that supposedly “neutral” policy analysis methods are value-laden (statement 26), and most are neutral on the statement that “any number can be leaned on” (18).

Statement 26: The purported ethical and political neutrality of policy analysis is an illusion masking the inherently value-laden character of any analytic method. -1 +1 +1 0 - 1 Statement 18: Any number can be leaned on. 0 0 +1 -2 0

0 All types of policy analysts accept a responsibility beyond providing good information. Also, they all believe that policy analysts must pay attention to the politics of the policies they propose. Thus, analysts agree that the complete policy analyst will recommend not only the best policy, but also the best political strategy for a client to follow (statement 25). They agree that they have a responsibility to help map out a strategy for gaining acceptance of the best policy choice (statement 29). And, they agree that their job is not only to provide good advice, but “to do good for society by helping get needed policies enacted (statement 36). Further, most believe that policy analysis should be an instrument for making progress toward what they view as the good society (statement 32). Thus, even the objective technicians see a role beyond the analysis of alternatives, even though they (alone among the types of analysts) would prefer not to get too involved in politics (see statements 35 and 39).

Statement 25: The complete policy analyst will not only recommend the best policy alternative but also the best political strategy with which the client can win the adoption and implementation of this alternative. +2 +4 +4 +4 +4

Statement 32: I believe that analysis should be an instrument for making progress toward what I view as the “good society.” +1 0 +2 +2 + I

0 All types of analysts reject the statement that technically bad analysis


is successful if it has an impact (statement 17) and that analysis is good if other analysts think i t is a “good piece of intellectual work” (statement 11). Most agree that success of analysis is based on the “accuracy of the estimate as tested by real world outcomes” (statement 13). All types of analysts, except one, reject the idea of shading analysis to favor a preferred outcome (statement 1).

Statement 17: If i t makes an impact it is successful, even if it is bad analysis technically. -4 -2 -1 -1 - 1

Statement 11: If other analysts think it’s a good piece of intellectual work, then it’s good. -2 -1 -1 -2 - 1

Statement 13: Success is based on the accuracy of the estimates as tested by real world outcomes. +2 +2 0 +2 0

RESPONDENT CHARACTERISTICS AND FACTOR TYPES

Table 3 gives the factors scores for each person who completed the Q-sorts, plus information about each respondent’s sex, employment location, and education. This table shows that groups of similar respondents-such as university-based analysts and researchers, and graduates of the Berkeley public policy school-tended to fall into the same categories of types of analysts.

The university-based analysts and researchers include seven at the Vinson Institute of Government at the University of Georgia, four at the Arkansas Institute of Government, one at the Policy Research Center at Georgia State University, and one at the Institute of Community and Area Development at the University of Georgia. Of these university-based analysts and researchers, six work in divisions or individual positions primarily concerned with applied policy research, and seven work in divisions or positions that provide more direct policy and management advice (technical assistance) to clients.

All six respondents working in research-oriented positions loaded on factor A, and two of them also loaded on factor B. Of the university-based respondents providing technical assistance, one loaded on factor A, one on factors A and B, one on factor B, and two on factor C . Also, two did not load significantly on any of the factors. This distribution of analysts and researchers shows that the respondents with doctoral degrees working as applied policy researchers function as objective technicians. However, other university- based respondents who work more directly with clients may view their roles much differently, functioning as an objective technician, client counselor, or issue activist.

The sorts show that most of the researchers and analysts at the University of Georgia’s Institute of Government are classified as objective technicians, but two of their four counterparts at the University of Arkansas at Little Rock sorted as issue advocates. This difference in orientation may reflect the fact that most of the respondents at the Georgia Institute of Government function

Policy Analysts’ Roles and Value Orientations 1 65 1

as policy researchers, while those in Arkansas are more likely to function as analysts providing technical assistance to particular clients.

However, location of employment seems unimportant for one group of respondents with a similar background: graduates of University of Califor- nia’s Graduate School of Public Policy. Although these analysts and researchers are scattered across city, county, regional, and state organizations, six of the nine sorted as issue activists, one as an ambivalent issue activist (factor D), and one as a client counselor. One does not load significantly on any factor. Thus, despite their different types of jobs, seven of the nine GSPP graduates have an orientation toward issue activism.

This clustering of GSPP graduates may reflect their common educational background, or may be attributed to other influences; it is possible that the Berkeley policy school attracts people who are concerned about specific policy issues and want to have an impact on society. After graduation, these analysts may seek out positions that give them the opportunity to be advocates for the issues that concern them. In short, the fact that most of the “activist analysts” were graduates of the Berkeley policy school may be the result of the education at that school or personal beliefs that led the respondents to attend that school and seek the jobs they have.13

Jenkins-Smith [ 1982, p. 951 noted, “Some scholars have held that the model of the client’s advocate is the rule in governmental bureaucracies.” He took this cue from Meltsner [1976, p. 1681. However, an examination of the distribution of bureaucracy-based analysts and researchers shows them represented in all of the factors, with only 7 of 18 respondents working in a government bureaucracy loading significantly as client counselors or client helpers.

The factor B is the most diverse group of respondents, including analysts and researchers from both California and Georgia. It contains two respondents who work for similar associations of local governments, plus a researcher working in a large state bureaucracy-two very different work settings. Factor B respondents have diverse academic backgrounds, with advanced degrees in public administration, social work, ecology, and education.

CONCLUSION

In this article, we have used Q-methodology to identify and describe five types of analysts, each with different views of their roles and different value orientations. These types of analysts are objective technicians, client counselors, issue activisits, ambivalent issue activists, and client helpers.

Using these research results, we are able to suggest answers to the three questions presented in our introduction. The first two questions concern the

l 3 A colleague who read a draft version of this article suggested that the Q-sorts may reflect, a t least in part, the commitment that different analysts have to the issues on which they work. Thus, if they work for organizations that deal with issues that engage them, analysts may be more inclined toward advocacy. Also, this person suggested that proximity to power may have an influence on the Q-sorts. Perhaps, the closer an analyst is to the politically powerful, the more likely that person is to be an advocate for the client. These propositions could best be tested through an extensive methodology such as survey research.


extent to which policy analysts and researchers resemble the ideal types suggested in the literature on the topic, and if the ideal types are not accurate, what analysts have in common and how they differ. We found that factor A analysts closely resemble Meltsner’s [ 19761 technicians and the objective technicians described by Jenkins-Smith [ 19821 and others; factor C analysts are much like the issue advocates of Jenkins-Smith [1982] and others; and factor E analysts are similar to Jenkins-Smith’s model of client advocates, though they lack the same degree of commitment to clients as suggested by the model. These client helpers view their jobs to be assisting their clients, but-like factor A analysts-they also favor objective, value-neutral analysis, and seem unwilling to sacrifice analytic integrity for promotion of their client’s interests.

The factor B analysts, client counselors, fall somewhere between the ideal-type objective technicians and client advocates. Even more than the client helpers, they are unwilling to define their jobs in terms of helping their clients obtain desired outcomes. Also, they resemble objective technicians in their devotion to objective analysis; thus, they lack much of the “advocacy” orientation of the ideal-type advocates described in the literature.

The factor D analysts seem to be torn between the values of factor A and factor C analysts. Ultimately, they function more as issue advocates who have greater concern about policy outcomes than the accuracy of their analytic products.

We also found that factor A analysts, the objective analysts, are not as blindly positivistic as is suggested by some critics of traditional policy analysis. They recognize that complex problems have multiple dimensions and answers, and they agree that their recommendations contend with alternatives in the context of a pluralist political system. Also, they agree that they have a responsibility to be involved as political strategists to help get the best policy options enacted, though they remain reluctant to get too involved in politics.

It appears that many policy analysts in our P sample seek to balance the ideal of providing objective, unbiased advice against the difficulty-or impossibility-of finding the one best answer to many policy problems. Although these analysts embrace many of the ideas underlying interpretative analysis, many of them function as advocates unwilling to compromise their analytic integrity, or as “producers of policy arguments.”

The third question concerns the characteristics of the respondents that seem most closely associated with types of analysts. These associations cannot be investigated conclusively using an intensive methodology like the Q-method; we cannot suggest what percentage of all analysts fall into different categories of analysts, nor even assert that we have identified all the different types of analysts. Also we cannot systematically test hypotheses about the independent variables that are associated with factor type as a dependent variable. However, the Q-method results can be used to help identify some characteristics that seem to be associated with the five analytic types.

We found that the university-based policy researchers are all factor A objective technicians despite differences in their educational specialties. However, university-based policy analysts (those working more directly


with clients on shorter term projects) are distributed among three different types of analysts.

The association of job location and analytic type-as found with the university-based policy researchers-is not reflected in factor C analysts, the issue activists. This group consists largely of graduates of the Berkeley Graduate School of Public Policy (GSPP). Of the nine GSPP graduates included in the P sample, seven loaded significantly on factor C or factor D, both issue activists, despite the fact that they work in different types of organizations.

In short, our research found that organization location seemed strongly associated with one type of policy analyst and researcher, and educational background was strongly associated with another type. To understand more about the influence of organization location and education on analytic role and value orientations, additional Q-sorts will be needed.

APPENDIX A: POLICY ANALYSTS ROLE AND VALUE ORIENTATIONS: SCORES O N Q STATEMENTS

#

1

2

3

4

5

6

7

8

Statement (Factor Scores) When I am doing a policy analysis of a complex issue and the facts do not clearly favor the alternative I think is correct, I may shade the analysis in favor of my preferred outcome if that does not undermine the analytic plausibility of the analysis. (C3) - 3 - 3 -1 +1 - 2 Politics is somebody else’s business. My main business is research, which is linked to policymaking. ( A l ) 0 - 3 -4 - 3 - 3 I am always looking for opportunities to shape policy in specific directions that I think are best. (C3) 0 -1 + 3 + 1 0 For policy analysts like me, clients are necessary evils. They provide the resources that allow me to work on interesting questions, but often they try to interfere with objective analysis. (A2) -1 -4 -3 -1 + 1 I am more concerned with the outcomes of policies I analyze rather than things like analytical integrity and responsibility to the client. (C2) -4 - 4 - 3 +2 - 3 If the human intellect could free itself from the fetters of belief and dogma, it could dig down to some bedrock of certainty. (A5) 0 - 2 - 3 0 0 If my agency provides an inhospitable climate for research, I will shift my niche by hopping to another. (A5) + l - 1 - 1 - 1 -2 Like physicians, analysts should “do no harm” to their clients; like attorneys, they should vigorously promote their clients’ interests. (B 1) - 3 -1 + I - 2 0


9

10

11

12

13

14

15

16

17

is 19

20

21

22

23

24

Value decisions are best left up to policy makers and need not nor should not be the subject of policy analysis. (AS) -2 -1 -4 -3 -3 I know that my future lies in protecting my client’s future. (Bl) -2 0 -1 -2 + 3 If other analysts think it’s a good picce of intellectual work, then it’s good. (A4) -2 -1 -1 -2 -1 My main job as an analyst is to provide the best possible case for my client’s preferred policy alternative. (BI) -2 0 -1 -4 + l Success is based on the accuracy of the estimates as tested by real world outcomes. (A4) +2 +2 0 +2 0 Analysts derive their legitimacy as participants in the formation of public policy from their clients, who hold elected or appointed office or who represent organized political interests. (B2) 0 + 1 0 -1 + l You are an intellectual eunuch if you don’t care i f it’s not acted on. Analysis is not an end to itself. (B4 and C4) + 1 0 +3 + 1 -1 The policymaking process is a struggle between clients with competing policy positions, and my policy analysis provides my client with a strategy and ammunition for the stuggle. (B5) + 1 +1 + 1 0 + 3 If it makes an impact it is successful, even if it is bad analysis technically. (B4 and C4) -4 -2 -1 -1 -1 Any number can be leaned on. (B5 and C5) 0 0 + 1 -2 0 Justice would be achieved through an adversarial process of give and take among advocates representing particular social interests. (B5 and C5) -1 +1 0 -2 + 2 If you come up with analysis that continually reflects your interests and not your client’s, you will fail. (B4) 0 +2 0 -1 +2 Policy analysts should take as their professional responsibility to enable policymakers to look in different ways at the nature of the social problems they have to address. (B3 and C3) +4 + 3 +2 +1 +1 Policy analysis may look like escape from politics, but really is a mask for the surreptitious exercise of power. (B5 and CS) -1 0 +1 0 -4 My work as a policy analyst fits into a pluralist policymaking system in which many competing actors have a part. (B5 and CS) + 3 + 3 + 3 + 3 + 3 The policy analyst is a producer of policy arguments, more similar to a lawyer than to an engineer or a scientist. (B3 and C3) -1 + 2 + I + 3 0


25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

The complete policy analyst will not only recommend the best policy alternative but also the best political strategy with which the client can win the adoption and implementation of this alternative. (B3) +2 +4 +4 + 4 +4 The purported ethical and political neutrality of policy analysis is an illusion masking the inherently value-laden character of any analytic method. (B5 and CS) - 1 + 1 + I 0 - 1 I see myself as an advocate for an idea or an issue in which I believe very strongly. (Cl) 0 -2 +2 +1 + I If an issue is very complex with no clear answer, I may shade my analysis in my client’s favor if doing so does not move the analysis beyond the pale of analytical plausibility. (B3) -3 -2 0 +2 0 Once I have figured out the best program alternative, my job is to map out and help implement a strategy for gaining acceptance of this policy choice. (Cl) +2 + 1 +2 +2 +4 I must relegate my policy preferences to a secondary position once I make a commitment to go to work for a client. (B2) + I +2 -2 -4 - 1 I care deeply about some problem or some group that is underrepresented in government, and that feeling affects my analysis. ( C l ) -1 - 1 +2 + 1 -4 I believe that analysis should be an instrument for making progress toward what I view as the “good society.” (C2) + l 0 + 2 +2 + 1 The proper role for the analyst is to provide objective advice about the consequences of proposed policies. (A3) +4 + 4 0 +4 +2 Usually there is one best solution to a policy problem I analyze. ( A l ) -2 -4 -3 -3 -2 I prefer to be free from politics so that I can develop the best program alternative that, I hope, will be selected on the basis of its objective merit. (A3) +2 0 -2 0 -3 My job is not only to provide good advice, but to do good for society by helping get needed policies enacted. (C4) +2 +1 +4 + 3 + 3 An analyst contributes to the good society, at least in the long run, by consistently providing unbiased advice even when it does not lead to the selection of personally favored policies. (A2) +3 + 3 0 0 +2 Analysts should strive to be objective and value-neutral. They should not let personal values or preferences affect their analysis of facts. ( A l ) + 3 +2 -2 0 -1 I prefer in my work to be insulated from the internal games of influence and policy disputes among governmental bureaus and agencies. (A3) +1 -2 -2 -1 -2


APPENDIX B: STATEMENTS REPRESENTING DIFFERENT DIMENSIONS OF THE Q-SAMPLE

Dimension Statements

A1 A2 A3 A4 A5

B1 B2 B3 B4 B5

c1 c2 c 3 c 4 c 5

B/C 3 B/C 4 B/C 5

2, 34, 38 4, 37 33, 35, 39 11, 13 6, 7, 9

8, 10, 12 14, 30 25, 28 20 16

27, 29, 31 5, 32 1, 3 36

21, 24 15, 17 18, 19, 22, 23, 26

We would like to thank Sally Coleman Selden, a DPA student a t the University of Georgia, for her outstanding assistance in carrying out this research. Also, we would like to invite readers to contact us if they would like to complete one of our Q-sorts. We will mail you a Q-sort that can be self-administered. After you complete it and return it to us, we will add you to the P sample.

DAN DURNING is a public service associate at the Carl Vinson Institute of Government and an adjunct professor in the Department of Political Science, University of Georgia. WILL OSUNA is a doctoral student in the Department of Political Science, University of Georgia, and the Carl Vinson Research Assistant in Public Adminis- tration.

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Policy analysts' roles and value orientations: An empirical investigation using Q methodology

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