Tag Archives: evidence and policy

Policy Analysis in 750 Words: policy analysis for marginalized groups in racialized political systems

Note: this post forms one part of the Policy Analysis in 750 words series overview.

For me, this story begins with a tweet by Professor Jamila Michener, about a new essay by Dr Fabienne Doucet, ‘Centering the Margins: (Re)defining Useful Research Evidence Through Critical Perspectives’:

Research and policy analysis for marginalized groups

For Doucet (2019: 1), it begins by describing the William T. Grant Foundation’s focus on improving the ‘use of research evidence’ (URE), and the key questions that we should ask when improving URE:

  1. For what purposes do policymakers find evidence useful?

Examples include to: inform a definition of problems and solutions, foster practitioner learning, support an existing political position, or impose programmes backed by evidence (compare with How much impact can you expect from your analysis?).

  1.   Who decides what to use, and what is useful?

For example, usefulness could be defined by the researchers providing evidence, the policymakers using it, the stakeholders involved in coproduction, or the people affected by research and policy (compare with Bacchi, Stone and Who should be involved in the process of policy analysis?).

  1. How do critical theories inform these questions? (compare with T. Smith)

First, they remind us that so-called ‘rational’ policy processes have incorporated research evidence to help:

‘maintain power hierarchies and accept social inequity as a given. Indeed, research has been historically and contemporaneously (mis)used to justify a range of social harms from enslavement, colonial conquest, and genocide, to high-stakes testing, disproportionality in child welfare services, and “broken windows” policing’ (Doucet, 2019: 2)

Second, they help us redefine usefulness in relation to:

‘how well research evidence communicates the lived experiences of marginalized groups so that the understanding of the problem and its response is more likely to be impactful to the community in the ways the community itself would want’ (Doucet, 2019: 3)

In that context, potential responses include to:

  1. Recognise the ways in which research and policy combine to reproduce the subordination of social groups.
  • General mechanisms include: the reproduction of the assumptions, norms, and rules that produce a disproportionate impact on social groups (compare with Social Construction and Policy Design).
  • Specific mechanism include: judging marginalised groups harshly according to ‘Western, educated, industrialized, rich and democratic’ norms (‘WEIRD’)
  1. Reject the idea that scientific research can be seen as objective or neutral (and that researchers are beyond reproach for their role in subordination).
  2. Give proper recognition to ‘experiential knowledge’ and ‘transdiciplinary approaches’ to knowledge production, rather than privileging scientific knowledge.
  3. Commit to social justice, to help ‘eliminate oppressions and to emancipate and empower marginalized groups’, such as by disrupting ‘the policies and practices that disproportionately harm marginalized groups’ (2019: 5-7)
  4. Develop strategies to ‘center race’, ‘democratize’ research production, and ‘leverage’ transdisciplinary methods (including poetry, oral history and narrative, art, and discourse analysis – compare with Lorde) (2019: 10-22)

Policy analysis in a ‘racialized polity’

A key way to understand these processes is to use, and improve, policy theories to explain the dynamics and impacts of a racialized political system. For example, ‘policy feedback theory’ (PFT) draws on elements from historical institutionalism and SCPD to identify the rules, norms, and practices that reinforce subordination.

In particular, Michener’s (2019: 424) ‘Policy Feedback in a Racialized Polity’ develops a ‘racialized feedback framework (RFF)’ to help explain the ‘unrelenting force with which racism and White supremacy have pervaded social, economic, and political institutions in the United States’. Key mechanisms include (2019: 424-6):

  1. Channelling resources’, in which the rules, to distribute government resources, benefit some social groups and punish others.
  • Examples include: privileging White populations in social security schemes and the design/ provision of education, and punishing Black populations disproportionately in prisons (2019: 428-32).
  • These rules also influence the motivation of social groups to engage in politics to influence policy (some citizens are emboldened, others alienated).
  1. Generating interests’, in which ‘racial stratification’ is a key factor in the power of interest groups (and balance of power in them).
  2. Shaping interpretive schema’, in which race is a lens through which actors understand, interpret, and seek to solve policy problems.
  3. The ways in which centralization (making policy at the federal level) or decentralization influence policy design.
  • For example, the ‘historical record’ suggests that decentralization is more likely to ‘be a force of inequality than an incubator of power for people of color’ (2019: 433).

Insufficient attention to race and racism: what are the implications for policy analysis?

One potential consequence of this lack of attention to race, and the inequalities caused by racism in policy, is that we place too much faith in the vague idea of ‘pragmatic’ policy analysis.

Throughout the 750 words series, you will see me refer generally to the benefits of pragmatism:

In that context, pragmatism relates to the idea that policy analysis consists of ‘art and craft’, in which analysts assess what is politically feasible if taking a low-risk client-oriented approach.

In this context, pragmatism may be read as a euphemism for conservatism and status quo protection.

In other words, other posts in the series warn against too-high expectations for entrepreneurial and systems thinking approaches to major policy change, but they should not be read as an excuse to reject ambitious plans for much-needed changes to policy and policy analysis (compare with Meltzer and Schwartz, who engage with this dilemma in client-oriented advice).

Connections to blog themes

This post connects well to:

 

 

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Policy Analysis in 750 Words: how much impact can you expect from your analysis?

This post forms one part of the Policy Analysis in 750 words series overview.

Throughout this series you may notice three different conceptions about the scope of policy analysis:

  1. ‘Ex ante’ (before the event) policy analysis. Focused primarily on defining a problem, and predicting the effect of solutions, to inform current choice (as described by Meltzer and Schwartz and Thissen and Walker).
  2. ‘Ex post’ (after the event) policy analysis. Focused primarily on monitoring and evaluating that choice, perhaps to inform future choice (as described famously by Weiss).
  3. Some combination of both, to treat policy analysis as a continuous (never-ending) process (as described by Dunn).

As usual, these are not hard-and-fast distinctions, but they help us clarify expectations in relation to different scenarios.

  1. The impact of old-school ex ante policy analysis

Radin provides a valuable historical discussion of policymaking with the following elements:

  • a small number of analysts, generally inside government (such as senior bureaucrats, scientific experts, and – in particular- economists),
  • giving technical or factual advice,
  • about policy formulation,
  • to policymakers at the heart of government,
  • on the assumption that policy problems would be solved via analysis and action.

This kind of image signals an expectation for high impact: policy analysts face low competition, enjoy a clearly defined and powerful audience, and their analysis is expected to feed directly into choice.

Radin goes on to describe a much different, modern policy environment: more competition, more analysts spread across and outside government, with a less obvious audience, and – even if there is a client – high uncertainty about where the analysis fits into the bigger picture.

Yet, the impetus to seek high and direct impact remains.

This combination of shifting conditions but unshifting hopes/ expectations helps explain a lot of the pragmatic forms of policy analysis you will see in this series, including:

  • Keep it catchy, gather data efficiently, tailor your solutions to your audience, and tell a good story (Bardach)
  • Speak with an audience in mind, highlight a well-defined problem and purpose, project authority, use the right form of communication, and focus on clarity, precision, conciseness, and credibility ( Smith)
  • Address your client’s question, by their chosen deadline, in a clear and concise way that they can understand (and communicate to others) quickly (Weimer and Vining)
  • Client-oriented advisors identify the beliefs of policymakers and anticipate the options worth researching (Mintrom)
  • Identify your client’s resources and motivation, such as how they seek to use your analysis, the format of analysis they favour (make it ‘concise’ and ‘digestible’), their deadline, and their ability to make or influence the policies you might suggest (Meltzer and Schwartz).
  • ‘Advise strategically’, to help a policymaker choose an effective solution within their political context (Thissen and Walker).
  • Focus on producing ‘policy-relevant knowledge’ by adapting to the evidence-demands of policymakers and rejecting a naïve attachment to ‘facts speaking for themselves’ or ‘knowledge for its own sake’ (Dunn).
  1. The impact of research and policy evaluation

Many of these recommendations are familiar to scientists and researchers, but generally in the context of far lower expectations about their likely impact, particularly if those expectations are informed by policy studies (compare Oliver & Cairney with Cairney & Oliver).

In that context, Weiss’ work is a key reference point. It gives us a menu of ways in which policymakers might use policy evaluation (and research evidence more widely):

  • to inform solutions to a problem identified by policymakers
  • as one of many sources of information used by policymakers, alongside ‘stakeholder’ advice and professional and service user experience
  • as a resource used selectively by politicians, with entrenched positions, to bolster their case
  • as a tool of government, to show it is acting (by setting up a scientific study), or to measure how well policy is working
  • as a source of ‘enlightenment’, shaping how people think over the long term (compare with this discussion of ‘evidence based policy’ versus ‘policy based evidence’).

In other words, researchers may have a role, but they struggle (a) to navigate the politics of policy analysis, (b) find the right time to act, and (c) to secure attention, in competition with many other policy actors.

  1. The potential for a form of continuous impact

Dunn suggests that the idea of ‘ex ante’ policy analysis is misleading, since policymaking is continuous, and evaluations of past choices inform current choices. Think of each policy analysis steps as ‘interdependent’, in which new knowledge to inform one step also informs the other four. For example, routine monitoring helps identify compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly, and if we can make a causal link between the policy solutions and outcomes. Its impact is often better seen as background information with intermittent impact.

Key conclusions to bear in mind

  1. The demand for information from policy analysts may be disproportionately high when policymakers pay attention to a problem, and disproportionately low when they feel that they have addressed it.
  2. Common advice for policy analysts and researchers often looks very similar: keep it concise, tailor it to your audience, make evidence ‘policy relevant’, and give advice (don’t sit on the fence). However, unless researchers are prepared to act quickly, to gather data efficiently (not comprehensively), to meet a tight brief for a client, they are not really in the impact business described by most policy analysis texts.
  3. A lot of routine, continuous, impact tends to occur out of the public spotlight, based on rules and expectations that most policy actors take for granted.

Further reading

See the Policy Analysis in 750 words series overview to continue reading on policy analysis.

See the ‘evidence-based policymaking’ page to continue reading on research impact.

ebpm pic

Bristol powerpoint: Paul Cairney Bristol EBPM January 2020

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Policy Analysis in 750 Words: Who should be involved in the process of policy analysis?

This post forms one part of the Policy Analysis in 750 words series overview.

Think of two visions for policy analysis. It should be primarily:

These choices are not mutually exclusive, but there are key tensions between them that should not be ignored, such as when we ask:

  • how many people should be involved in policy analysis?
  • whose knowledge counts?
  • who should control policy design?

Perhaps we can only produce a sensible combination of the two if we clarify their often very different implications for policy analysis. Let’s begin with one story for each and see where they take us.

A story of ‘evidence-based policymaking’

One story of ‘evidence based’ policy analysis is that it should be based on the best available evidence of ‘what works’.

Often, the description of the ‘best’ evidence relates to the idea that there is a notional hierarchy of evidence according to the research methods used.

At the top would be the systematic review of randomised control trials, and nearer the bottom would be expertise, practitioner knowledge, and stakeholder feedback.

This kind of hierarchy has major implications for policy learning and transfer, such as when importing policy interventions from abroad or ‘scaling up’ domestic projects.

Put simply, the experimental method is designed to identify the causal effect of a very narrowly defined policy intervention. Its importation or scaling up would be akin to the description of medicine, in which the evidence suggests the causal effect of a specific active ingredient to be administered with the correct dosage. A very strong commitment to a uniform model precludes the processes we might associate with co-production, in which many voices contribute to a policy design to suit a specific context (see also: the intersection between evidence and policy transfer).

A story of co-production in policymaking

One story of ‘co-produced’ policy analysis is that it should be ‘reflexive’ and based on respectful conversations between a wide range of policymakers and citizens.

Often, the description is of the diversity of valuable policy relevant information, with scientific evidence considered alongside community voices and normative values.

This rejection of a hierarchy of evidence also has major implications for policy learning and transfer. Put simply, a co-production method is designed to identify the positive effect – widespread ‘ownership’ of the problem and commitment to a commonly-agreed solution – of a well-discussed intervention, often in the absence of central government control.

Its use would be akin to a collaborative governance mechanism, in which the causal mechanism is perhaps the process used to foster agreement (including to produce the rules of collective action and the evaluation of success) rather than the intervention itself. A very strong commitment to this process precludes the adoption of a uniform model that we might associate with narrowly-defined stories of evidence based policymaking.

Where can you find these stories in the 750-words series?

  1. Texts focusing on policy analysis as evidence-based/ informed practice (albeit subject to limits) include: Weimer and Vining, Meltzer and Schwartz, Brans, Geva-May, and Howlett (compare with Mintrom, Dunn)
  2. Texts on being careful while gathering and analysing evidence include: Spiegelhalter
  3. Texts that challenge the ‘evidence based’ story include: Bacchi, T. Smith, Hindess, Stone

 

How can you read further?

See the EBPM page and special series ‘The politics of evidence-based policymaking: maximising the use of evidence in policy

There are 101 approaches to co-production, but let’s see if we can get away with two categories:

  1. Co-producing policy (policymakers, analysts, stakeholders). Some key principles can be found in Ostrom’s work and studies of collaborative governance.
  2. Co-producing research to help make it more policy-relevant (academics, stakeholders). See the Social Policy and Administration special issue ‘Inside Co-production’ and Oliver et al’s ‘The dark side of coproduction’ to get started.

To compare ‘epistemic’ and ‘reflexive’ forms of learning, see Dunlop and Radaelli’s ‘The lessons of policy learning: types, triggers, hindrances and pathologies

My interest has been to understand how governments juggle competing demands, such as to (a) centralise and localise policymaking, (b) encourage uniform and tailored solutions, and (c) embrace and reject a hierarchy of evidence. What could possibly go wrong when they entertain contradictory objectives? For example:

  • Paul Cairney (2019) “The myth of ‘evidence based policymaking’ in a decentred state”, forthcoming in Public Policy and Administration(Special Issue, The Decentred State) (accepted version)
  • Paul Cairney (2019) ‘The UK government’s imaginative use of evidence to make policy’, British Politics, 14, 1, 1-22 Open AccessPDF
  • Paul Cairney and Kathryn Oliver (2017) ‘Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?’ Health Research Policy and Systems (HARPS), DOI: 10.1186/s12961-017-0192-x PDF
  • Paul Cairney (2017) “Evidence-based best practice is more political than it looks: a case study of the ‘Scottish Approach’”, Evidence and Policy, 13, 3, 499-515 PDF

 

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Policy Analysis in 750 words: William Dunn (2017) Public Policy Analysis

Please see the Policy Analysis in 750 words series overview before reading the summary. This book is a whopper, with almost 500 pages and 101 (excellent) discussions of methods, so 800 words over budget seems OK to me. If you disagree, just read every second word.  By the time you reach the cat hanging in there baby you are about 300 (150) words away from the end.

Dunn 2017 cover

William Dunn (2017) Public Policy Analysis 6th Ed. (Routledge)

Policy analysis is a process of multidisciplinary inquiry aiming at the creation, critical assessment, and communication of policy-relevant knowledge … to solve practical problemsIts practitioners are free to choose among a range of scientific methods, qualitative as well as quantitative, and philosophies of science, so long as these yield reliable knowledge’ (Dunn, 2017: 2-3).

Dunn (2017: 4) describes policy analysis as pragmatic and eclectic. It involves synthesising policy relevant (‘usable’) knowledge, and combining it with experience and ‘practical wisdom’, to help solve problems with analysis that people can trust.

This exercise is ‘descriptive’, to define problems, and ‘normative’, to decide how the world should be and how solutions get us there (as opposed to policy studies/ research seeking primarily to explain what happens).

Dunn contrasts the ‘art and craft’ of policy analysts with other practices, including:

  1. The idea of ‘best practice’ characterised by 5-step plans.
  • In practice, analysis is influenced by: the cognitive shortcuts that analysts use to gather information; the role they perform in an organisation; the time constraints and incentive structures in organisations and political systems; the expectations and standards of their profession; and, the need to work with teams consisting of many professions/ disciplines (2017: 15-6)
  • The cost (in terms of time and resources) of conducting multiple research and analytical methods is high, and highly constrained in political environments (2017: 17-8; compare with Lindblom)
  1. The too-narrow idea of evidence-based policymaking
  • The naïve attachment to ‘facts speak for themselves’ or ‘knowledge for its own sake’ undermines a researcher’s ability to adapt well to the evidence-demands of policymakers (2017: 68; 4 compare with Why don’t policymakers listen to your evidence?).

To produce ‘policy-relevant knowledge’ requires us to ask five questions before (Qs1-3) and after (Qs4-5) policy intervention (2017: 5-7; 54-6):

  1. What is the policy problem to be solved?
  • For example, identify its severity, urgency, cause, and our ability to solve it.
  • Don’t define the wrong problem, such as by oversimplifying or defining it with insufficient knowledge.
  • Key aspects of problems including ‘interdependency’ (each problem is inseparable from a host of others, and all problems may be greater than the sum of their parts), ‘subjectivity’ and ‘artificiality’ (people define problems), ‘instability’ (problems change rather than being solved), and ‘hierarchy’ (which level or type of government is responsible) (2017: 70; 75).
  • Problems vary in terms of how many relevant policymakers are involved, how many solutions are on the agenda, the level of value conflict, and the unpredictability of outcomes (high levels suggest ‘wicked’ problems, and low levels ‘tame’) (2017: 75)
  • ‘Problem-structuring methods’ are crucial, to: compare ways to define or interpret a problem, and ward against making too many assumptions about its nature and cause; produce models of cause-and-effect; and make a problem seem solve-able, such as by placing boundaries on its coverage. These methods foster creativity, which is useful when issues seem new and ambiguous, or new solutions are in demand (2017: 54; 69; 77; 81-107).
  • Problem definition draws on evidence, but is primarily the exercise of power to reduce ambiguity through argumentation, such as when defining poverty as the fault of the poor, the elite, the government, or social structures (2017: 79; see Stone).
  1. What effect will each potential policy solution have?
  • Many ‘forecasting’ methods can help provide ‘plausible’ predictions about the future effects of current/ alternative policies (Chapter 4 contains a huge number of methods).
  • ‘Creativity, insight, and the use of tacit knowledge’ may also be helpful (2017: 55).
  • However, even the most-effective expert/ theory-based methods to extrapolate from the past are flawed, and it is important to communicate levels of uncertainty (2017: 118-23; see Spiegelhalter).
  1. Which solutions should we choose, and why?
  • ‘Prescription’ methods help provide a consistent way to compare each potential solution, in terms of its feasibility and predicted outcome, rather than decide too quickly that one is superior (2017: 55; 190-2; 220-42).
  • They help to combine (a) an estimate of each policy alternative’s outcome with (b) a normative assessment.
  • Normative assessments are based on values such as ‘equality, efficiency, security, democracy, enlightenment’ and beliefs about the preferable balance between state, communal, and market/ individual solutions (2017: 6; 205 see Weimer & Vining, Meltzer & Schwartz, and Stone on the meaning of these values).
  • For example, cost benefit analysis (CBA) is an established – but problematic – economics method based on finding one metric – such as a $ value – to predict and compare outcomes (2017: 209-17; compare Weimer & Vining, Meltzer & Schwartz, and Stone)
  • Cost effectiveness analysis uses a $ value for costs, but compared with other units of measurement for benefits (such as outputs per $) (2017: 217-9)
  • Although such methods help us combine information and values to compare choices, note the inescapable role of power to decide whose values (and which outcomes, affecting whom) matter (2017: 204)
  1. What were the policy outcomes?
  • ‘Monitoring’ methods help identify (say): levels of compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly (such as on clearly defined ‘inputs’ such as public sector wages), and if we can make a causal link between the policy inputs/ activities/ outputs and outcomes (2017: 56; 251-5)
  • Monitoring is crucial because it is so difficult to predict policy success, and unintended consequences are almost inevitable (2017: 250).
  • However, the data gathered are usually no more than proxy indicators of outcomes. Further, the choice of indicators reflect what is available, ‘particular social values’, and ‘the political biases of analysts’ (2017: 262)
  • The idea of ‘evidence based policy’ is linked strongly to the use of experiments and systematic review to identify causality (2017: 273-6; compare with trial-and-error learning in Gigerenzer, complexity theory, and Lindblom).
  1. Did the policy solution work as intended? Did it improve policy outcomes?
  • Although we frame policy interventions as ‘solutions’, few problems are ‘solved’. Instead, try to measure the outcomes and the contribution of your solution, and note that evaluations of success and ‘improvement’ are contested (2017: 57; 332-41).  
  • Policy evaluation is not an objective process in which we can separate facts from values.
  • Rather, values and beliefs are part of the criteria we use to gauge success (and even their meaning is contested – 2017: 322-32).
  • We can gather facts about the policy process, and the impacts of policy on people, but this information has little meaning until we decide whose experiences matter.

Overall, the idea of ‘ex ante’ (forecasting) policy analysis is a little misleading, since policymaking is continuous, and evaluations of past choices inform current choices.

Policy analysis methods are ‘interdependent’, and ‘knowledge transformations’ describes the impact of knowledge regarding one question on the other four (2017: 7-13; contrast with Meltzer & Schwartz, Thissen & Walker).

Developing arguments and communicating effectively

Dunn (2017: 19-21; 348-54; 392) argues that ‘policy argumentation’ and the ‘communication of policy-relevant knowledge’ are central to policymaking’ (See Chapter 9 and Appendices 1-4 for advice on how to write briefs, memos, and executive summaries and prepare oral testimony).

He identifies seven elements of a ‘policy argument’ (2017: 19-21; 348-54), including:

  • The claim itself, such as a description (size, cause) or evaluation (importance, urgency) of a problem, and prescription of a solution
  • The things that support it (including reasoning, knowledge, authority)
  • Incorporating the things that could undermine it (including any ‘qualifier’, the communication of uncertainty about current knowledge, and counter-arguments).

The key stages of communication (2017: 392-7; 405; 432) include:

  1. ‘Analysis’, focusing on ‘technical quality’ (of the information and methods used to gather it), meeting client expectations, challenging the ‘status quo’, albeit while dealing with ‘political and organizational constraints’ and suggesting something that can actually be done.
  2. ‘Documentation’, focusing on synthesising information from many sources, organising it into a coherent argument, translating from jargon or a technical language, simplifying, summarising, and producing user-friendly visuals.
  3. ‘Utilization’, by making sure that (a) communications are tailored to the audience (its size, existing knowledge of policy and methods, attitude to analysts, and openness to challenge), and (b) the process is ‘interactive’ to help analysts and their audiences learn from each other.

 

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Policy analysis and policy theory: systems thinking, evidence based policymaking, and policy cycles

Dunn (2017: 31-40) situates this discussion within a brief history of policy analysis, which culminated in new ways to express old ambitions, such as to:

  1. Use ‘systems thinking’, to understand the interdependence between many elements in complex policymaking systems (see also socio-technical and socio-ecological systems).
  • Note the huge difference between (a) policy analysis discussions of ‘systems thinking’ built on the hope that if we can understand them we can direct them, and (b) policy theory discussions that emphasise ‘emergence’ in the absence of central control (and presence of multi-centric policymaking).
  • Also note that Dunn (2017: 73) describes policy problems – rather than policymaking – as complex systems. I’ll write another post (short, I promise) on the many different (and confusing) ways to use the language of complexity.
  1. Promote ‘evidence based policy, as the new way to describe an old desire for ‘technocratic’ policymaking that accentuates scientific evidence and downplays politics and values (see also 2017: 60-4).

In that context, see Dunn’s (47-52) discussion of comprehensive versus bounded rationality:

  • Note the idea of ‘erotetic rationality’ in which people deal with their lack of knowledge of a complex world by giving up on the idea of certainty (accepting their ‘ignorance’), in favour of a continuous process of ‘questioning and answering’.
  • This approach is a pragmatic response to the lack of order and predictability of policymaking systems, which limits the effectiveness of a rigid attachment to ‘rational’ 5 step policy analyses (compare with Meltzer & Schwartz).

Dunn (2017: 41-7) also provides an unusually useful discussion of the policy cycle. Rather than seeing it as a mythical series of orderly stages, Dunn highlights:

  1. Lasswell’s original discussion of policymaking functions (or functional requirements of policy analysis, not actual stages to observe), including: ‘intelligence’ (gathering knowledge), ‘promotion’ (persuasion and argumentation while defining problems), ‘prescription’, ‘invocation’ and ‘application’ (to use authority to make sure that policy is made and carried out), and ‘appraisal’ (2017: 42-3).
  2. The constant interaction between all notional ‘stages’ rather than a linear process: attention to a policy problem fluctuates, actors propose and adopt solutions continuously, actors are making policy (and feeding back on its success) as they implement, evaluation (of policy success) is not a single-shot document, and previous policies set the agenda for new policy (2017: 44-5).

In that context, it is no surprise that the impact of a single policy analyst is usually minimal (2017: 57). Sorry to break it to you. Hang in there, baby.

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Policy Analysis in 750 words: Beryl Radin, B (2019) Policy Analysis in the Twenty-First Century

Please see the Policy Analysis in 750 words series overview before reading the summary. As usual, the 750-word description is more for branding than accuracy.

Beryl Radin (2019) Policy Analysis in the Twenty-First Century (Routledge)

Radin cover 2019

The basic relationship between a decision-maker (the client) and an analyst has moved from a two-person encounter to an extremely complex and diverse set of interactions’ (Radin, 2019: 2).

Many texts in this series continue to highlight the client-oriented nature of policy analysis (Weimer and Vining), but within a changing policy process that has altered the nature of that relationship profoundly.

This new policymaking environment requires new policy analysis skills and training (see Mintrom), and limits the applicability of classic 8-step (or 5-step) policy analysis techniques (2019: 82).

We can use Radin’s work to present two main stories of policy analysis:

  1. The old ways of making policy resembled a club, or reflected a clear government hierarchy, involving:
  • a small number of analysts, generally inside government (such as senior bureaucrats, scientific experts, and – in particular- economists),
  • giving technical or factual advice,
  • about policy formulation,
  • to policymakers at the heart of government,
  • on the assumption that policy problems would be solved via analysis and action.
  1. Modern policy analysis is characterised by a more open and politicised process in which:
  • many analysts, inside and outside government,
  • compete to interpret facts, and give advice,
  • about setting the agenda, and making, delivering, and evaluating policy,
  • across many policymaking venues,
  • often on the assumption that governments have a limited ability to understand and solve complex policy problems.

As a result, the client-analyst relationship is increasingly fluid:

In previous eras, the analyst’s client was a senior policymaker, the main focus was on the analyst-client relationship, and ‘both analysts and clients did not spend much time or energy thinking about the dimensions of the policy environment in which they worked’ (2019: 59). Now, in a multi-centric policymaking environment:

  1. It is tricky to identify the client.
  • We could imagine the client to be someone paying for the analysis, someone affected by its recommendations, or all policy actors with the ability to act on the advice (2019: 10).
  • If there is ‘shared authority’ for policymaking within one political system, a ‘client’ (or audience) may be a collection of policymakers and influencers spread across a network containing multiple types of government, non-governmental actors, and actors responsible for policy delivery (2019: 33).
  • The growth in international cooperation also complicates the idea of a single client for policy advice (2019: 33-4)
  • This shift may limit the ‘face-to-face encounters’ that would otherwise provide information for – and perhaps trust in – the analyst (2019: 2-3).
  1. It is tricky to identify the analyst
  • Radin (2019: 9-25) traces, from the post-war period in the US, a major expansion of policy analysts, from the notional centre of policymaking in federal government towards analysts spread across many venues, inside government (across multiple levels, ‘policy units’, and government agencies) and congressional committees, and outside government (such as in influential think tanks).
  • Policy analysts can also be specialist external companies contracted by organisations to provide advice (2019: 37-8).
  • This expansion shifted the image of many analysts, from a small number of trusted insiders towards many being treated as akin to interest groups selling their pet policies (2019: 25-6).
  • The nature – and impact – of policy analysis has always been a little vague, but now it seems more common to suggest that ‘policy analysts’ may really be ‘policy advocates’ (2019: 44-6).
  • As such, they may now have to work harder to demonstrate their usefulness (2019: 80-1) and accept that their analysis will have a limited impact (2019: 82, drawing on Weiss’ discussion of ‘enlightenment’).

Consequently, the necessary skills of policy analysis have changed:

Although many people value systematic policy analysis (and many rely on economists), an effective analyst does not simply apply economic or scientific techniques to analyse a problem or solution, or rely on one source of expertise or method, as if it were possible to provide ‘neutral information’ (2019: 26).

Indeed, Radin (2019: 31; 48) compares the old ‘acceptance that analysts would be governed by the norms of neutrality and objectivity’ with

(a) increasing calls to acknowledge that policy analysis is part of a political project to foster some notion of public good or ‘public interest’, and

(b)  Stone’s suggestion that the projection of reason and neutrality is a political strategy.

In other words, the fictional divide between political policymakers and neutral analysts is difficult to maintain.

Rather, think of analysts as developing wider skills to operate in a highly political environment in which the nature of the policy issue is contested, responsibility for a policy problem is unclear, and it is not clear how to resolve major debates on values and priorities:

  • Some analysts will be expected to see the problem from the perspective of a specific client with a particular agenda.
  • Other analysts may be valued for their flexibility and pragmatism, such as when they acknowledge the role of their own values, maintain or operate within networks, communicate by many means, and supplement ‘quantitative data’ with ‘hunches’ when required (2019: 2-3; 28-9).

Radin (2019: 21) emphasises a shift in skills and status

The idea of (a) producing new and relatively abstract ideas, based on high control over available information, at the top of a hierarchical organisation, makes way for (b) developing the ability to:

  • generate a wider understanding of organisational and policy processes, reflecting the diffusion of power across multiple policymaking venues
  • identify a map of stakeholders,
  • manage networks of policymakers and influencers,
  • incorporate ‘multiple and often conflicting perspectives’,
  • make and deliver more concrete proposals (2019: 59-74), while recognising
  • the contested nature of information, and the practices sued to gather it, even during multiple attempts to establish the superiority of scientific evidence (2019: 89-103),
  • the limits to a government’s ability to understand and solve problems (2019: 95-6),
  • the inescapable conflict over trade-offs between values and goals, which are difficult to resolve simply by weighting each goal (2019: 105-8; see Stone), and
  • do so flexibly, to recognise major variations in problem definition, attention and networks across different policy sectors and notional ‘stages’ of policymaking (2019: 75-9; 84).

Radin’s (2019: 48) overall list of relevant skills include:

  1. ‘Case study methods, Cost- benefit analysis, Ethical analysis, Evaluation, Futures analysis, Historical analysis, Implementation analysis, Interviewing, Legal analysis, Microeconomics, Negotiation, mediation, Operations research, Organizational analysis, Political feasibility analysis, Public speaking, Small- group facilitation, Specific program knowledge, Statistics, Survey research methods, Systems analysis’

They develop alongside analytical experience and status, from the early career analyst trying to secure or keep a job, to the experienced operator looking forward to retirement (2019: 54-5)

A checklist for policy analysts

Based on these skills requirements, the contested nature of evidence, and the complexity of the policymaking environment, Radin (2019: 128-31) produces a 4-page checklist of – 91! – questions for policy analysts.

For me, it serves two main functions:

  1. It is a major contrast to the idea that we can break policy analysis into a mere 5-8 steps (rather, think of these small numbers as marketing for policy analysis students, akin to 7-minute abs)
  2. It presents policy analysis as an overwhelming task with absolutely no guarantee of policy impact.

To me, this cautious, eyes-wide-open, approach is preferable to the sense that policy analysts can change the world if they just get the evidence and the steps right.

Further Reading:

  1. Iris Geva-May (2005) ‘Thinking Like a Policy Analyst. Policy Analysis as a Clinical Profession’, in Geva-May (ed) Thinking Like a Policy Analyst. Policy Analysis as a Clinical Profession (Basingstoke: Palgrave)

Although the idea of policy analysis may be changing, Geva-May (2005: 15) argues that it remains a profession with its own set of practices and ways of thinking. As with other professions (like medicine), it would be unwise to practice policy analysis without education and training or otherwise learning the ‘craft’ shared by a policy analysis community (2005: 16-17). For example, while not engaging in clinical diagnosis, policy analysts can draw on 5-step process to diagnose a policy problem and potential solutions (2005: 18-21). Analysts may also combine these steps with heuristics to determine the technical and political feasibility of their proposals (2005: 22-5), as they address inevitable uncertainty and their own bounded rationality (2005: 26-34; see Gigerenzer on heuristics). As with medicine, some aspects of the role – such as research methods – can be taught in graduate programmes, while others may be better suited to on the job learning (2005: 36-40). If so, it opens up the possibility that there are many policy analysis professions to reflect different cultures in each political system (and perhaps the venues within each system).

  1. Vining and Weimar’s take on the distinction between policy analysis and policy process research

 

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Understanding Public Policy 2nd edition

All going well, it will be out in November 2019. We are now at the proofing stage.

I have included below the summaries of the chapters (and each chapter should also have its own entry (or multiple entries) in the 1000 Words and 500 Words series).

2nd ed cover

titlechapter 1chapter 2chapter 3chapter 4.JPG

chapter 5

chapter 6chapter 7.JPG

chapter 8

chapter 9

chapter 10

chapter 11

chapter 12

chapter 13

 

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Filed under 1000 words, 500 words, agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, public policy

Evidence-informed policymaking: context is everything

I thank James Georgalakis for inviting me to speak at the inaugural event of IDS’ new Evidence into Policy and Practice Series, and the audience for giving extra meaning to my story about the politics of ‘evidence-based based policymaking’. The talk (using powerpoint) and Q&A is here:

 

James invited me to respond to some of the challenges raised to my talk – in his summary of the event – so here it is.

I’m working on a ‘show, don’t tell’ approach, leaving some of the story open to interpretation. As a result, much of the meaning of this story – and, in particular, the focus on limiting participation – depends on the audience.

For example, consider the impact of the same story on audiences primarily focused on (a) scientific evidence and policy, or (b) participation and power.

Normally, when I talk about evidence and policy, my audience is mostly people with scientific or public health backgrounds asking why do policymakers ignore scientific evidence? I am usually invited to ruffle feathers, mostly by challenging a – remarkably prevalent – narrative that goes like this:

  • We know what the best evidence is, since we have produced it with the best research methods (the ‘hierarchy of evidence’ argument).
  • We have evidence on the nature of the problem and the most effective solutions (the ‘what works’ argument).
  • Policymakers seems to be ignoring our evidence or failing to act proportionately (the ‘evidence-policy barriers’ argument).
  • Or, they cherry-pick evidence to suit their agenda (the ‘policy based evidence’ argument).

In that context, I suggest that there are many claims to policy-relevant knowledge, policymakers have to ignore most information before making choices, and they are not in control of the policy process for which they are ostensibly in charge.

Limiting participation as a strategic aim

Then, I say to my audience that – if they are truly committed to maximising the use of scientific evidence in policy – they will need to consider how far they will go to get what they want. I use the metaphor of an ethical ladder in which each rung offers more influence in exchange for dirtier hands: tell stories and wait for opportunities, or demonise your opponents, limit participation, and humour politicians when they cherry-pick to reinforce emotional choices.

It’s ‘show don’t tell’ but I hope that the take-home point for most of the audience is that they shouldn’t focus so much on one aim – maximising the use of scientific evidence – to the detriment of other important aims, such as wider participation in politics beyond a reliance on a small number of experts. I say ‘keep your eyes on the prize’ but invite the audience to reflect on which prizes they should seek, and the trade-offs between them.

Limited participation – and ‘windows of opportunity’ – as an empirical finding

NASA launch

I did suggest that most policymaking happens away from the sphere of ‘exciting’ and ‘unruly’ politics. Put simply, people have to ignore almost every issue almost all of the time. Each time they focus their attention on one major issue, they must – by necessity – ignore almost all of the others.

For me, the political science story is largely about the pervasiveness of policy communities and policymaking out of the public spotlight.

The logic is as follows. Elected policymakers can only pay attention to a tiny proportion of their responsibilities. They delegate the rest to bureaucrats at lower levels of government. Bureaucrats lack specialist knowledge, and rely on other actors for information and advice. Those actors trade information for access. In many cases, they develop effective relationships based on trust and a shared understanding of the policy problem.

Trust often comes from a sense that everyone has proven to be reliable. For example, they follow norms or the ‘rules of the game’. One classic rule is to contain disputes within the policy community when actors don’t get what they want: if you complain in public, you draw external attention and internal disapproval; if not, you are more likely to get what you want next time.

For me, this is key context in which to describe common strategic concerns:

  • Should you wait for a ‘window of opportunity’ for policy change? Maybe. Or, maybe it will never come because policymaking is largely insulated from view and very few issues reach the top of the policy agenda.
  • Should you juggle insider and outsider strategies? Yes, some groups seem to do it well and it is possible for governments and groups to be in a major standoff in one field but close contact in another. However, each group must consider why they would do so, and the trade-offs between each strategy. For example, groups excluded from one venue may engage (perhaps successfully) in ‘venue shopping’ to get attention from another. Or, they become discredited within many venues if seen as too zealous and unwilling to compromise. Insider/outsider may seem like a false dichotomy to experienced and well-resourced groups, who engage continuously, and are able to experiment with many approaches and use trial-and-error learning. It is a more pressing choice for actors who may have only one chance to get it right and do not know what to expect.

Where is the power analysis in all of this?

image policy process round 2 25.10.18

I rarely use the word power directly, partly because – like ‘politics’ or ‘democracy’ – it is an ambiguous term with many interpretations (see Box 3.1). People often use it without agreeing its meaning and, if it means everything, maybe it means nothing.

However, you can find many aspects of power within our discussion. For example, insider and outsider strategies relate closely to Schattschneider’s classic discussion in which powerful groups try to ‘privatise’ issues and less powerful groups try to ‘socialise’ them. Agenda setting is about using resources to make sure issues do, or do not, reach the top of the policy agenda, and most do not.

These aspects of power sometimes play out in public, when:

  • Actors engage in politics to turn their beliefs into policy. They form coalitions with actors who share their beliefs, and often romanticise their own cause and demonise their opponents.
  • Actors mobilise their resources to encourage policymakers to prioritise some forms of knowledge or evidence over others (such as by valuing scientific evidence over experiential knowledge).
  • They compete to identify the issues most worthy of our attention, telling stories to frame or define policy problems in ways that generate demand for their evidence.

However, they are no less important when they play out routinely:

  • Governments have standard operating procedures – or institutions – to prioritise some forms of evidence and some issues routinely.
  • Many policy networks operate routinely with few active members.
  • Certain ideas, or ways of understanding the world and the nature of policy problems within it, becomes so dominant that they are unspoken and taken for granted as deeply held beliefs. Still, they constrain or facilitate the success of new ‘evidence based’ policy solutions.

In other words, the word ‘power’ is often hidden because the most profound forms of power often seem to be hidden.

In the context of our discussion, power comes from the ability to define some evidence as essential and other evidence as low quality or irrelevant, and therefore define some people as essential or irrelevant. It comes from defining some issues as exciting and worthy of our attention, or humdrum, specialist and only relevant to experts. It is about the subtle, unseen, and sometimes thoughtless ways in which we exercise power to harness people’s existing beliefs and dominate their attention as much as the transparent ways in which we mobilise resources to publicise issues. Therefore, to ‘maximise the use of evidence’ sounds like an innocuous collective endeavour, but it is a highly political and often hidden use of power.

See also:

I discussed these issues at a storytelling workshop organised by the OSF:

listening-new-york-1-11-16

See also:

Policy in 500 Words: Power and Knowledge

The politics of evidence-based policymaking

Palgrave Communications: The politics of evidence-based policymaking

Using evidence to influence policy: Oxfam’s experience

The UK government’s imaginative use of evidence to make policy

 

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Filed under agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, Psychology Based Policy Studies, public policy, Storytelling