The United States has required formal standardized testing and set a minimum standard of curriculum in public education since 1965 with the “Elementary and Secondary Education Act”. It was in 2001 that the “No Child Left Behind Act” tied school funding to students performance on the test, which has become an issue of contention between policy makers and service providers and beneficiaries. This past week, a new standardized test was provided to New York City students that was based on the recently developed and rolled out Common Core Standards with supplemental curriculum. The test was developed by the National Governors Association’s (NGA) Center for Best Practices in conjunction with the Council of Chief State School Officers (CCSSO) and adopted by almost every state.

The NGA is a collective organization of the 55 governors of states, territories and commonwealth in the United States and public policy experts who advice policy makers on a range of issues of state and national importance including public education provision. The Education division of the NGA is made up of roughly six experts who have economics, and/or public policy backgrounds.[i] The CCSSO focuses mainly on education policy and is made up of key education policy makers from each state, for instance John King Jr. the Commissioner of Education in New York, and boasts of an Executive Director who is accredited with playing an integral role in the development of the Common core standards, “…directed the Council’s standards program- the work that would later become the Common Core State Standards”.[ii] The director was also a long time employee of Pearsons, the program that provides the testing and profits off the test preparation materials.

In the area of standardized testing, there does not seem to be room for doubt that policy analysts play a role in directing policy. Both, the standards that have been set and the evaluative measures to be taken, have been developed (in the very least) collaboratively with the NGA and CCSSO and public policy makers. In these instances the two organizations acted as experts in the education field and directed policy makers, and were nothing short of instrumental in the policy process.

Nancy Shulock contends that analysts are providers of ideas, “policy analysis has changed, right along with the policy process, to become the provider of ideas and frames, to help sustain the discourse that shapes citizen preferences, and to provide the appearance of rationality in an increasingly complex political environment” (Shulock, p240). With this definition of policy analysis, one cannot argue that analysts who provide information and set standards of a public service, as the NGA and CCSSO has, these organizations have seized a part of the decision making process, if only the provision of alternatives presented to the decision maker.

This seizure of the policy process in education, from standard setting to evaluation, creates a new environment where policy analysts can influence decision making, very different than the requirements that Lawrence Mead set out in his article The Interaction Problem in Policy Analysis. Mead argues analysts need, “goals that can be sharply defined, separated from programs, or distinguished from subsidy of the affected interests” (Mead, 54).  The goals of the standard setting and testing have not only held up through economic reasoning, but are pushed through by such logic: it is a low cost assessment tool that is objective and provides the state the ability to compare the success of a large scale public service provision, unlike any other program. [iii] Since the organizations themselves defined the goals, and coordinate the implementations of the programs, these requirements cannot apply to them.

The perennial debate about whether policy analysts influence policy-making might only be solvable when one looks at a policy decision through a defined lens. For standard setting and evaluation in public school provision, two organizations that supply policy makers with expert information also played a major role in designing and determining standards and the evaluation measures that would be taken to determine the success of those standards, and thus were instrumental in the policy making process. Although other stakeholders, like teachers, parents and administrators, were consulted after the adoption of these policies for adaptation in the implementation stage, the main tenets of the policies were developed and implemented at the recommendation of policy “informers” or analysts in both the agenda setting and decision making stages.



[i] NGA Website: http://www.nga.org/files/live/sites/NGA/files/pdf/NGAOrgChart.pdf

; http://www.nga.org/cms/home/about/contact-info.html

[ii] CCSSO Website: http://www.ccsso.org/Who_We_Are/Leadership_Team.html

[iii] Hoxby, Caroline. “The Cost of Accountability”. NBER Working Paper. April 2002. http://standardizedtests.procon.org/sourcefiles/the-cost-of-accountability.pdf

Shulock, Nancy, “The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce so Much of It?” Journal of Policy Analysis and Management, 18(2), 1999.

Mead, Lawrence M., “The Interaction Problem in Policy Analysis,” Policy Sciences, 16(1), 1983.

Andrea

How can policy research distort and obfuscate social and economic realities? In this week’s readings, Shulock (1999) presents the paradox of society’s heavy investment in policy analysis, despite substantive evidence and theories suggesting that analysis is not used to make better policies. Mead (1983) finds that analysis can interact with problems to make them different and more difficult to solve than they would be without analysis. Mead partially points to the fact that policy analysts measure success and effectiveness based on the criteria of policy chosen, rather than carried out.

The disconnect between optimal choice and optimal implementation is at least partially to blame for the lack of effectiveness attributed to policy analysis, and adherence to conservative models of incremental change prevent systemic change from being achieved.

For those in the field, these are rather bleak pronouncements: a growing and heavily invested in professional industry that is not effective? This seems like bad news for academic institutions that teach these professionals their craft, government and other bodies that rely on their skills and output, and, of course, policy analysts themselves.

Despite these findings, cities continue to rely on analysts (and the legislators they inform) as the drivers of urban policy agendas. In many cities, this is a continuation of the status quo policy formula and policymaking players – mayor, city council, issue advocates, etc. But other cities have changed how policy is made, either by changing participatory processes or introducing new policymaking authorities into the existing political landscape.

In March 2013, the governor of Michigan appointed an emergency fiscal manager to take over Detroit’s finances. The role of the emergency manager, Kevyn Orr, a Washington bankruptcy lawyer, is to improve services and bring fiscal discipline to the state’s largest city, including making decisions on how to stem the city’s mounting cash shortfall and reduce an estimated $14 billion in long-term liabilities. Orr will have the final word on Detroit’s budget expenditures and fiscal policies, and can make decisions about public salaries and service cuts.

Despite the seeming single authoritativeness of this role, Orr’s position as emergency manager is consistent with Mead’s analysis of the challenges and inefficiencies of the roles of policy analysts. Mead finds, analysts are not independent enough from bureaucracy to have political influence in their own right; they are most influential when their influence is by way of their work, becoming entrepreneurs for programs. Orr’s position reinforces this finding: his influence and position comes from a bureaucratic mandate, and the exertion of Orr’s power is as an “entrepreneur” for improving the fiscal situation in Detroit.

The kinds of long-term changes Orr makes will be primarily incremental. Those changes that are not, such as cutting salaries or eliminating inefficient services, will shed light on the poor job being done by government. These actions and roles are also consistent with Mead’s assessment of the role of policy analysts.

Here, we can return to the concern’s raised by Shulock (1999):  Will Orr’s actions based on his analysis of the fiscal crisis in Detroit make a significant contribution to the long-term solution of the city’s pressing policy problems?

Using her “interpretative” framework, Shulock might argue that if Orr is successful in using analysis and action as a language for framing political discourse, a legitimate rationalization of legislative action, and a symbol of legitimate decision-making processes, he will succeed in reshaping Detroit’s policy landscape and eradicating its dysfunction.

Resources:
Mead, Lawrence M., “The Interaction Problem in Policy Analysis,” Policy Sciences, 16(1), 1983.

Shulock, Nancy, “The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce So Much of It?” Journal of Policy Analysis and Management, 18(2), 1999. (BB)

Vlasic, Bill. “Lawyer Outlines Challenges in New Job Fixing Detroit” The New York Times. March 25, 2013. 

Yaccino, Steven. “Detroit’s Leaders Carry on, but Know Who’s Really in Charge.” The New York Times. April 12, 2013.           

Last week, Herndon, Ash and Pollin (2013) released a paper challenging the findings of a widely cited study by Reinhart and Rogoff (2010) that was broadly used by political commentators and policymakers in support of European austerity measures and in budget debates in the U.S. The original findings argued that high debt to GDP ratios (namely, at a threshold of over 90%) lead to lower average GDP growth. Herndon, Ash and Pollin replicated this study, finding three types of errors which, if corrected, result in a much smaller difference between average growth rates on either side of the 90% debt to GDP ratio (Herndon et al., 2013). One error was an Excel coding mistake in which the authors excluded five countries that resulted in a -0.3 percentage point error in the average GDP growth in the highest public debt to GDP category. Another error involved selectively excluding time periods for certain countries (within the overall time period they examine) in which these countries had high debt and solid growth. Lastly, their measure of average real growth for each country is, according to Herndon, Ash and Pollin, unconventional as they take an average rather than weighting each year of data. This construct also strongly affects the overall results. This is a clear example of a research study that many in the mainstream media and public, as well as policy domain have accepted as conclusive without critically examining assumptions behind the study or how straightforward the implications actually are.

Schram and Soss (2002), in their analysis of research of the effects of the Temporary Assistance for Needy Families (TANF) program, argue that the “facts” of these impacts (e.g., 60% fewer people are on welfare than pre-TANF) are politically interpreted and their meanings far from obvious. Similarly, some have argued that although it has been widely accepted that higher debt causes lower economic growth, the causation is actually backwards; low growth motivates countries to issue debt in order to stimulate economic growth (Konczal, 2013). This possibility is acknowledged by Reinhart and Rogoff, but the lasting message that they clearly intend their study to get across is that high debt is unhealthy for the economy. Schram (2002) argues that a rampant problem in most empirically oriented research, is that “being an academic first often means couching one’s research in ostensibly neutral terms and allowing the ‘facts to speak for themselves.’” Reinhart and Rogoff suggest that higher debt acts as a signal of risk to investors. This suggestion is couched in neutral terms, but they provide no evidence to support this causal direction and go on to suggest other vulnerabilities associated with debt while not acknowledging their political orientation or what some might call a somewhat obvious alternative explanation. Beyond the particulars of the variable constructs and outright coding errors, how findings are interpreted was not clearly a question of debate for the original study's authors.

Open questions remain as to how this study may have been conducted or interpreted differently by researchers whose political orientations play a more overt their research. When research is informed by practice or policymaking, as in Schram’s “Weak Program,” do researchers and research consumers tend to be more critical of methods, constructs and interpretations?

References

Herndon, T., Ash, M., & Pollin, R. (2013). Does High Public Debt Consistently Stifle Economic Growth?: A Critique of Reinhart and Rogoff. Political Economy Research Institute. Amherst, MA.

Konczal, M. (2013). Shocking Paper Claims that Microsoft Excel Coding Error is Behind the Reinhart-Rogoff Study on Debt. Business Insider. Retrieved from http://www.businessinsider.com/thomas-herndon-michael-ash-and-robert-pollin-on-reinhart-and-rogoff-2013-4

Reinhart, C. M., & Rogoff, K. S. (2010). Growth in a Time of Debt.

Schram, S. F. (2002). Praxis for the Poor. New York, NY: New York University Press.

Schram, S. F., & Soss, J. (2002). Success Stories: Welfare Reform, Policy Discourse, and the Politics of Research. In S. F. Schram (Ed.), Praxis for the Poor (pp. 186–2000). New York: New York University Press.

Zoé

One view on the question of what is the role of policy research
comes from Lawrence Mead [1983]. In “The Interaction Problem in Policy
Analysis,” he argues that when economic analysis is applied to solving a
problem, it tends to create barriers to solving the problem. Policy analysis
that contributes to making the problem more difficult to solve is the
‘interaction problem,’ according to Mead. The root of the interaction problem is
found in the theoretical orientation that lies beneath economic analysis: “an
agnostic view of policy goals, stress on optimization, use of mathematical
models, [and] microeconomic assumptions about behavior” [46]. Some ways,
identified by Mead, that would prevent the interaction problem include:
importing goals from other disciplines into economic analysis; base analytic
goals on evidence from practices as oppose to deriving the goals from existing
theory; allow for analysis and political ideology to coexist as one. 
 
Mead’s argument fails to consider the case where applying
economic analysis to a problem can actually lead to lowering barriers to solving
the problem. In other words, analysis could in fact make the problem less
difficult to solve, diminishing the interaction problem. Consider, the author of
this précis was part of an economic policy consultant team that gathered to
examine the effects of 2009’s American Recovery and Reinvestment Act [ARRA] in transportation on social well-being of demographic groups. Using economic theory  as a tool to predict how the investment decision would impact firms and  demographic groups, we were aware that the investment could change behavior of  firms in one of three ways: lead to no change in behavior in terms of hiring,  lead to some changes, lead to big changes. To assess the theory, we tracked the  pathway of the investment. The pathway played out like this: federal investment  gets filtered to the state government; the state distributes the funds to  businesses; enterprises hire people; the people they hire are those first in queue; those first in queue hold seniority; those who held seniority are  predominantly white men [PolicyLink, 2010]. We found that without attention to  who is not in queue, or gender and racial dynamics, the investment decision  reinforced the status quo—employment disparities between demographic  groups—regardless of whether that outcome was intended or not. We can see from the example that without the economic analysis the devastating consequence of  the decision would not have been identified. On the flip side, with  identification, this could make the problem of employment disparities less  intractable to solve. My point here is that this is evidence that contradicts the argument presented by Mead.

 Another view on the question of what is the role of policy
research comes from Nancy Shulock [1999]. In “The Paradox of Policy Analysis,”  she argues that despite the increase in the production of policy analysis, its’  use by policymakers is quite limited. Part of the problem lies in the fact that  the conventional view on use of policy analysis is narrow and outdated. Shulock  presents a broader view and purpose. One purpose that she identifies is that it  can be used for ‘framing the political discourse’ [229]. The example I used  above fits into this conception. The economic analysis of ARRA impact in
transportation on social well-being of demographic groups was featured as part
of a Congressional Hearing on Transportation Equity in Minnesota. The hearing
was held at a Church and attended by media outlets. By entering the analysis in
the hearing, it became part of the democratic process. The analysis informed
residents, people from multiple faith backgrounds, and congressional leaders on
the potential impacts of the policy decision. Meanwhile, the analysis framed the
political discourse on transportation. The hearing took place on the eve of
the reauthorization of ARRA   investment in transportation opportunity. Well positioned, the analysis planted perspectives and information with federal lawmakers. That information informed their negotiations on additional measures that needed to be put into place to ensure that transportation equity was maximized. This is an example that meets the criteria for one of the purposes of policy analysis identified by Shulock.

 
References
 PolicyLink.  2010, June. “Equitable Recovery in Minnesota: Transportation.” Oakland, CA: PolicyLink.

 Shulock,  Nancy. 1999. “The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce So Much of It?” Journal of
Policy Analysis and Management. Vol. 18, No. 2.

Mead, Lawrence. 1983. “The Interaction Problem in Policy Analysis.” Policy
Sciences (16).

While policy analysis has been often understood as a rational, linear, clear process based on elegant theoretical frameworks and welfare economics tools that provide the basis for taking decisions, the reality of policy making has repeatedly shown that not only the policy process is indeed messier but equally, that the analysis of this process is often too restricted in accommodating and integrating the realities of decision making. Perhaps the shift from rational choice models towards more dynamic pluralist ones has been an effort to rethink the analysis process by encompassing a more realistic approach of what policy analysis can offer. Still, one can wonder what is the role of policy analysis is in an era characterized by the "triumph of the postmodern sensibility in the domain of policy," which favors anecdotes over policy substance, pessimism over the incrementalist's optimism, passion over reason, and media sound bites over reasoned political discourse (Shulock, 2003 and Kirp, 1992 cited in Shulock). Is traditional policy analysis dead or is it reinventing itself as a discipline in order to reflect the actual policy process?

            Shulock (2003) provides an interesting insight to the question above when she argues that:

“The problem, is only that policy analysts, policymakers, and observers alike do not recognize policy analysis for what it is. Policy analysis has changed, right along with the policy process, to become the provider of ideas and frames, to help sustain the discourse that shapes citizen preferences, and to provide the appearance of rationality in an increasingly complex political environment.” (p. 240). Under this view, policy analysis has a larger than what we usually perceive role. It is less rational-objective, although it provides the “appearance” of rationality, and more ideologically biased; in that sense, it does not provide solutions to problems but it becomes a weapon in the battle to shape debate, claim jurisdiction, and gain public approval of legislative activity.

            Perhaps the recent story on the influential paper by Ken Rogoff and Carmen Reinhart

 “Growth in a Time of Debt” can shed further light on the ways policy making is influenced by analysis but also on the ways analysis is often charged with ideological claims. Rogoff and Reinhart presented the idea that when a country's ratio of debt to gross domestic product reaches 90% lower economic growth is on the horizon. This idea has been extremely influential in shaping austerity policies in the US but also in the Eurozone. A new study by Herdon et al (2013) finds that Rogoff and Reinhart made several mistakes that invalidate their thesis.[1] Reinhart and Rogoff admitted their bad calculation but denied claims that the errors were made intentionally. Certainly, judging if the mistake was intentional or not matters but it is hard to determine. What appears though of greater importance is the dialectic between scientific and ideological claims. In their response, Rogoff and Reinhart maintain that their main thesis, that there is a causal relationship between depth ratio and economic growth, although based on a false calculation is still relevant. But acknowledging this causal relationship seems to steam out of ideological beliefs rather than science. As Krugman showcases in a recent blog, countries ran up high debts as a consequence of their growth slowdowns, not the other way around.[2]

            Obviously the above causality matters in terms of policy making: if slow growth is the result of high depth then the austerity policies pursued in the Eurozone and the US make sense. If on the other hand, slow growth is attributed to other factors then increasing public depth might be a tactic to combat slow growth. In both scenarios, the answer is not clear. In that sense, Shulock’s claim that policy analysis already involves discourse, introduces ideas into politics, and affects policy outcomes. But it does so in a very different way while posing an important question: Is the role of the policy analyst, expert or academic impartial or one that should acknowledge ideological underpinnings? At the same time, does recognizing the potential bias in policy analysis will enhance the power of analysis of the discipline or would it blurry further its role into the policy decision making process? Certainly, answering these questions is far from obvious. Perhaps a redefinition of what is policy analysis is required to do so. In that sense, the problem shifts from the policy analysis as a discipline and becomes an issue of how we perceive policy analysis and its role. If we view policy analysis as the guide to the right solution amongst different alternatives then Rogoff and Reinhart do bear enormous responsibility for influencing and ultimately shaping policy decisions. If on the other hand, we perceive policy analysis as a laboratory of ideas, then Rogoff and Reinhart’s mistake suddenly becomes less important as we account for the ideological bias within their argument. While a shift towards the second definition will result in a loss of credibility for many of the solutions advanced through policy analysis, it will nevertheless acknowledge the non-neutral ideas and assumptions accompanying it.

References

Krugman, Paul, 2013. http://krugman.blogs.nytimes.com/2013/04/16/reinhart-rogoff-continued/

Rogoff and Reinhart. 2012. “Growth in a Time of Dept.” National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Shedlock, Mike. 2013. Excel Spreadsheets, Krugman, and a Question of Logic.

Shulock, Nancy, “The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce So Much of It?” Journal of Policy Analysis and Management, 18(2), 1999.



[1] They made a spreadsheet error that resulted in their leaving five countries out of an all-important average of countries with higher than 90% debt-to-GDP ratios. By restoring the full average, the UMass authors say, the growth rate for countries in that range becomes 2.2%, not the -0.1% cited by Rogoff and Reinhart (Shedlock, 2013).


[2] http://krugman.blogs.nytimes.com/2013/04/16/reinhart-rogoff-continued/

In “The Paradox of Policy Analysis: If It Is Not Used? Why Do We Produce So Much of It?” Nancy Shulock addresses these dual questions by arguing that the role of policy analysis in the policy making process has changed. It is no longer being used for problem solving as was originally intended; rather policy analysis supports and promotes discourse among policy actors by highlighting and clarifying specific issues. Lawrence Mead in “The Interaction Problem in Policy Analysis” explains why in the interaction of analysis and problems in the policy making process causes problems to change. While both authors are clearly discussing different issues, in addressing these issues they allude to a much deeper issue in policy analysis that is the dominance of economic theory in policy analysis. I have two concerns regarding this issue: firstly as policy analysis addresses issues that affect multiple aspects of human life, stronger consideration should be given to other equally relevant areas of theory. Secondly much of mainstream economic theory can be criticized for making assumptions that are unrealistic and unreflective of the real world therefore to allow an entire analytical field to be guided by these theories are a grave mistake. In this paper building on some of the arguments raised in Mead (1983) and Shulock (1999) I argue that policy analysis is not being used as a problem-solving tool because it is based on methods that rely on unrealistic assumption that generate results with limited real-world applications.

Mead (1983) asserts that the common criticisms of the use of economic paradigm are in the realism of its assertions and the calculations required. He references Wildavsky (1979), Lindbolm (1959), Trible (1972) and Allison and Halgrave (1971 and 1975) in summarizing the key arguments against the dominance of economic theory in policy analysis. Economic analysis assumes; political decisions are aimed at satisfying optimal not salient constituents, there are no limits on the information that policy makers can access, as economic consequences are easiest to measure policy analysis ignores other value areas, and it ignores the administrative and implementation dimensions of policy making. Perhaps no-where else are these issues blatantly clearer than in the design and implementation of unemployment policy. Unemployment policy is intended to achieve a single goal that is to reduce unemployment. Based on this goal a myriad of policies have been designed and implemented from employer-focused policies to worker-centered policies such as unemployment insurance program.

Despite its name Unemployment Insurance is not only intended to provide workers with income protection during job loss its larger goal is to keep workers in the labor force and actively looking for new employment. From this perspective its aim is simply to keep unemployment low. Possibly from its inception this program had been criticized for not achieving its goal largely because of weaknesses in the design of the policy. In addressing the issue of unemployment analyst sort specifically to find ways to induce people to find new employment as quickly as possible so they included restrictions on the length of time and quantity of benefits received. This was directly based on the assumption that rational workers facing reduced income would strive to re-enter formal employment as quickly possible. What was instead observed was that workers often chose to stay unemployed for as long as it was legally possible and loss of skill actually resulted in exit from the labor force entirely. In fact most states eventually increased benefit durations and replacement rates based on yet another misguided assumption that workers did not re-enter employment and in some cases left the labor force because the job-search time was too short. Very few economists and even less policy analysts in this area have considered the fact that workers cannot act rationally.

Rational choice requires among other things perfect knowledge about the existence and results of all possible alternatives. Human being in general and in this case workers specifically simply do not possess the processing capacity to collect and evaluate all possibilities therefore it is impossible for us to think and act rationally in the economic sense. If one applies a more behavioral or socio/psychological perspective which would assume that the actions of the worker will be guided by a more complex string of factors both internal such as emotion and self satisfaction to external the need to provide shelter and food then the outcomes of decisions regarding policy can be better analyzed. Not to mention emphasis in the analysis and design of policy will shift from influencing the organism to examining how the organism is affected, which will certainly improve the analysis and design of policy.

While Shulock (1999) does make the valid point that though policy analysis is no longer being used for its original purpose it is still being used. One must ask: Why was the shift necessary in the first place? The answer I would offer is that the product of policy analysis is often so misleading due to its unrealistic base assumptions that it has simply been relegated to the role of information provision, even in this role I would be weary of its ability as well.

References

Shulock, Nancy, “The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce So Much of It?” Journal of Policy Analysis and Management, 18(2), 1999

Mead, Lawrence M., “The Interaction Problem in Policy Analysis,” Policy Sciences, 16(1), 1983

Claude Joseph 

This essay argues that no democracy can be representative unless its bureaucracy is representative. Such a claim challenges two dominant contentious approaches in public policy. The first is the rational paradigm that stresses the comprehensive and problem-solving model in policy analysis. The second is the constructivism, a post-positivist approach that sees policy analysis as a battle over meaning, framing and symbol. Policy analysts, in the first model, are neutral actors that devise policies based on scientific principles such as cost-benefit analysis. Whereas, the second model views policy analysts as contributors to the democratic process not via problem-solving, but rather by framing issues to improve public discourse.

Both views show – implicitly and explicitly – the inescapable role of policy analysis in society, which is indeed an undeniable fact. Nancy Shulock in “The Paradox of Policy Analysis,” and David Weimer in “Enriching Public Discourse: Policy Analysis in Representative Democracies” both demonstrate the critical importance of policy analysis.  To Shulock, policy analysis is a tool of the democratic process. Likewise, Weimer (2002) contends that “policy analysts can make a contribution to debate by encouraging a more dynamic view of the world” (p. 62). He goes further to say that policy analysts contribute to distributional values by speaking for the less-representative interests. How so? The author’s response is that this can be achieved by using cost-benefit analysis, because “cost-benefit analysis forces consideration of diffuse interests that often remain silent” (p. 63).

Nothing is farther from the truth than an approach aiming at promoting the public interest by relying on an efficiency-driven technique such as cost-benefit analysis. The sealed bidding technique used under mayor Rudy Giuliani administration to contract out public services in New York is a case in point. The sealed bidding method, which limits the discretionary power of bureaucrats, turn out to favour big corporations to the detriment of minority business enterprises (MBEs). In contrast to big businesses, MBEs do not possess sufficient expertise and money to compete for contracts. As it happens, a democratic society with a bureaucracy that relies exclusively on efficiency as a means to distribute resources can end up being an instrument used by the well-off at the expense of the “diffuse interests that often remain silent.”

The constructivist approach, although it rejects the comprehensive and problem-solving perspective, is not an alternative however. The constructivist theorists opt for deliberation so policies can emerge from consensus in, say, community. Again, such a process will give an upper hand to those able to articulate and convey better their ideas in communities.

While Weimer emphasizes the importance of policy analysis to foster participation, he does not grasp the best way that can occur. One ideal solution is what Donald Kinsley in 1944 referred to as representative bureaucracy. The fundamental premise of representative bureaucracy is that active representation, or the selection of civil servants whose social backgrounds are similar to those of the people whom they serve, leads to active representation wherein the bureaucrat is expected to press and advocate for the interests of those he is presumed to represent. In other words, the concept of representative bureaucracy, according to Selden (1997), suggests that a bureaucracy that employs a cross section of American society will produce policy outcomes and outputs that reflect the interests and needs of all groups. Thus, a representative bureaucracy is a bureaucracy that reflects diversity of the general population, and it implies a symbolic commitment to equal access to power (Selden, 1997).

For example, Meier and Steward (1992) found that the presence of African-American schoolteachers, known as street level bureaucrats, had a significant effect on policy outcomes favoring African-American students. Likewise, analysing the Farmers Home Administration’s (FmHA) Rural Loans Program, Sally Coleman Selden found that districts that employ more African Americans, Hispanics, Asian Americans, Native American and women award more rural housing loans to these groups.

Pointing out the pervasiveness of policy analysis, Dolan and Rosenbloom (2003) argues that American bureaucracy makes more rules than congress and the state legislature make laws, and most disputes are adjudicated in administrative hearing than civil matters decided by the courts. Therefore, given this fact, a representative bureaucracy does not only legitimize policies but also make democracy a concept not devoid of practical substance. 



-Comment-

Claude,

Sealed bidding is a procurement practice which is used by a number of federal and state agencies in order to force them to take the bid  submitted by the lowest responsible bidder. I agree with you, that this practice can lead to the exclusion of Minority and Women-Owned Enterprises, who are often smaller and more expensive than non-certifed business. However, it also leads to the exclusion of politically connected firms who place higher bids counting on their connections with administrators to seal the deal. In this way, it gives a "voice" to the taxpayer, whose interests can sometimes be overridden during the procurement process.  In this interpretation, I think that sealed bidding can fit nicely into the idea of 'representative bureaucracy' as an extension of the traditional representative democracy (characterized only by the representation of  constituent interests by officials and government edifices) although not necessarily into the demographical and culturally responsive model that you are cultivating.

Just a thought.