Results from the CLEAR Road Test

Comparing participation: Results from the CLEAR road test

Report No 2

Report prepared for the Council of Europe Conference:

“Tools for strengthening democratic participation at local level”

Tampere, 28-29 June 2006

Valeria Guarneros (De Montfort University, UK) Vivien Lowndes (De Montfort University, UK) Lawrence Pratchett (De Montfort University, UK) Gerry Stoker (University of Manchester, UK)

23rd June 2006 Introduction

This report is the second analysis of the CLEAR road test. While the first report concentrated upon the experience of applying the CLEAR tool, and the lessons that have emerged for its future development, this report is concerned with analysing and interpreting the actual results from that test. Using the CLEAR framework, the report explores how participation profiles differ between localities and the various ways in which these profiles might be constructed. It complements the diagnosis process that the road test participants have already undertaken by offering a comparison analysis. Its main aim, therefore, is to challenge participants to reflect further upon the shape of participation in their areas and the strategies they might adopt to adjust their existing profiles.

This report does not provide any background information on the CLEAR road test as this detail is available in the first report. Instead, it concentrates on developing a method for analysing the information produced by the CLEAR process, and offers some preliminary comparisons on this basis.

Comparing diagnoses – limitations and strengths

From the outset, it is important to be aware of the type of information being analysed. The evidence that this analysis is based upon comes from the reports produced by each of the municipalities that participated in the CLEAR road test. In preparing these reports, each municipality drew upon data from a range of sources, including:

 Existing secondary source material produced as part of the municipality’s normal activities  Existing information that had already been collected by the municipality specifically in relation to participation initiatives  Information produced by other tiers of government, or by third parties  Interviews or focus groups with municipal employees and politicians  Surveys of citizens and the organisations of civil society  Focus groups with citizens or the organisations of civil society  The perceptions and informed opinions of those completing the process including, in some cases, the analytical insights of consultants

This information was collected as part of a self-diagnosis process rather than for the purpose of developing comparative metrics. As a consequence, the data is highly context dependent, providing a range of qualitative and quantitative information on the locality that only has meaning in that municipality. It would be inappropriate to compare separate components of that information across municipalities or to try and interpret its meaning outside of that context.

For the purposes of comparison, therefore, the information from the road test has significant limitations. The data has not been collected or presented in a

2 standardised form and does not lend itself to comparison of individual variables. There are no single quantifiable indicators that can be compared across all municipalities, or even a selection of them, on a like by like basis. It is also important to note that the tool was not designed to generate such information: the tool is for self-diagnosis rather than for the purposes of generating a league table of participation, either within or between countries. The nature of self-diagnosis means that the information presented by the participants is deliberatively self-critical. Each participating municipality has not simply assembled a range of objective facts or observations about participation in their locality but also developed a critical reflection of those observations. It is both inappropriate and unfair to attempt any sort of classification or subjective comparison of these self-critical reflections.

At the same time, however, the self diagnosis process offers a number of significant strengths to the comparative process. First, the information being compared is not derived from one source but has been developed from a wide range of sources that provide for both richer observations and triangulation of evidence. This range of sources suggests that evidence on which the analysis is based has higher level of reliability than most comparisons based on a single set of survey results. Second, the way in which municipalities have operationalised the CLEAR tool, using a variety of sources, ensures that the evidence is addressing the framework directly, thereby enhancing the validity of the evidence. Third, the process of self-diagnosis provides contextually relevant information about where those most able to influence participation policy see the strengths and weaknesses of their current municipalities. Consequently, from the perspective of seeking to identify broad policy trends in participation across Europe, it provides a unique insight into contemporary perceptions and potential policy responses. It is these strengths that this analysis builds on.

The method adopted

In order to make a comparison between the reports of different municipalities, it was first necessary to order the data contained in them. The ordering process took three stages.

1. After carefully reading the reports, their contents were inserted into a set of matrices containing the code of each participant municipality and the answer given for each question. The entries comprised key words or numbers contained in the original reports. This set of matrices worked as a guide to identify the key points in each municipality’s report.

2. Based on these matrices, brief summaries were prepared for each municipality, organized under each of the CLEAR headings.

3. By using the matrices and the summaries, a clearer picture was obtained from the different municipalities. This ordering of data, enabled the authors to make a judgment about how each municipality was performing

3 with respect to each component of CLEAR. The criteria used in making the judgments were as follows:

 Was the question answered?  Were additional references or examples included to help explain the answer further?  What was the implication of the answer for the participation diagnosis?

The point of these assessments was not to allocate raw scores but to arrive at a profile for each municipality across the five CLEAR components. Consequently, each municipality was assumed to have an initial score of 100. The final score for each municipality was then derived by allocating per cent scores across each of the five CLEAR components, in relation to the questions above. The derived scores are summarised in Appendix 1.

By following this process, the authors were able to identify the strengths and weakness of the model design. These strengths and weaknesses related in part to the way in which the municipalities interpreted the questions, the quality and extent of answers contained in the reports and the methods used to implement the model.

The results compared

What should be the appropriate profile for a municipality within CLEAR? It is tempting to assume that all factors in the CLEAR framework should be equally distributed and that any deviation from that equal distribution should be subject to correction. From this assumption, policy responses to a CLEAR diagnosis would seek automatically to build up those areas which register low and, possibly, to diminish the effects of higher scoring components, in order to achieve balance. However, such an assumption misses a fundamental point in the CLEAR framework: the framework is derived from an analysis of participation in different localities and takes, as its starting point, the understanding that all localities are different. This difference means that citizens’ resources, cultures of trust and reciprocity and networks of civil society all vary. As a consequence, the integration of civil society into public life and the extent to which public authorities will need to promote and respond to public engagement will also be different across localities. If the very simple point that all localities are different is accepted, then it is inevitable that the balance of different components in the CLEAR framework will also vary.

An important precondition of the analysis that follows, therefore, is that there is no perfect balance to be achieved between the components of CLEAR. It is up to each municipality to determine what the appropriate balance should be and to develop responses that might help to achieve that balance. It follows that this balance, in terms of both reality and what may be deemed desirable,

4 may vary over time as well as place. As a diagnostic tool, therefore, CLEAR is expected to be subject to several iterations in any one locality.

The comparison developed here is not seeking to offer any judgment on whether the balance in particular municipalities is correct or, indeed, in which direction it should be changing. The purpose of the comparison is much simpler. First, the analysis shows that variation does indeed exist between localities and explores the extent to which there is any systematic variation that can be identified. Second, it also challenges each participating municipality to reflect upon whether the balance ascribed to it is correct. Third, it has the potential to provoke municipalities and, indeed, the Council of Europe, to consider the various policy responses that might improve participation. Consequently, it offers another iteration in the self-diagnosis process.

The analysis draws upon the scores assigned to each municipality by the research team, following the method set out above. The raw scores on which the following charts are based are set out in Appendix 1. It is worth reminding readers that these scores are relative within municipalities rather than being scores derived as a result of comparison across them. We are not comparing differences between municipalities, therefore, on any one component of the CLEAR framework. The comparison is only relevant in terms of the distribution of scores across the municipality for each case. Consequently, the comparison is about the relative emphasis being given to different components of the CLEAR framework between municipalities, rather than an absolute score for an individual component.

Comparison by country

In comparing across countries, we are not seeking to draw to conclusions about the relative strengths or weaknesses of one country compared with another. Instead, the focus is more upon identifying commonalities across all countries and core themes that appear to be relevant in particular countries.

Chart 1 provides a full breakdown of the variations across all 23 municipalities that participated in the road test, using the data provided in appendix 1 (it should be noted at this point that the cases are not offered in any particular order). Immediately, it is clear that the municipalities in the five countries show considerable variation in terms of their CLEAR profile.

5 Chart 1 - Municipal variations on CLEAR

100%

C 90%

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L 70%

60% E 50% 40% A 30% 20% R 10% 0%

These differences are not simply a feature of the country but are locally specific. Charts 2-6 break down the variations by country. For each country we provide a brief commentary on the variations that emerge from these charts.

Chart 2 - Finland

C 100%

90%

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60% E 50%

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A 30%

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R 10% 0% Tampere Hämeelinna Imatra

Chart 2 shows the differences between the three participating municipalities in Finland. A feature of this table that strikes almost immediately is the relative consistency of the ‘Can do’ component across all three municipalities. While Tampere accords slightly more emphasis to the resources of its citizens, all three are at similar levels, representing around one fifth of the distribution between the five CLEAR components. However, the distribution of the other components varies much more. Imatra, for example, appears to place greater emphasis on the ‘ask to’ component than Tampere or Hämeenlinna. Overall,

6 Finnish municipalities do not place a great deal of emphasis upon the ‘responded to’ component of CLEAR, although Hämeenlinna does have a more equally distributed profile than the others.

Chart 3 - Netherlands

100% C 90%

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0% Utrecht Arnhem Zoetermeer Deurne Dantumadeel

The differences for Dutch municipalities are much more striking, as shown by Chart 3. Utrecht, in particular, contrasts with other localities in the Netherlands, giving much greater emphasis to the ‘can do’ and ‘responded to’ components than others. Two interesting points emerge from information provided, however. First, with the exception of Dantumadeel, Dutch municipalities are characterized by a perception of low levels of trust among citizens (especially trust in the municipality) and concerns about community spirit. This finding is significant, not because it is necessarily true (that is not the purpose of the tool) but because, if the municipality perceives low levels of trust among citizens, it will assume different approaches to participation than if it perceived high levels of trust.

Second, many of the municipalities place great emphasis upon the latter two components of the CLEAR framework. Dutch municipalities seem to be particularly conscious of the need to find innovative ways of engaging citizens (the ‘ask to’ component) and of then demonstrating responsiveness. This emphasis may well reflect a response to perceived low levels of trust and community spirit, with municipalities working especially hard to compensate for shortfalls in that area. However, the policy implications are again significant: the emphasis upon increasing participation opportunities and responding to engagement may well help build trust but, as the final section of this report shows, there are also other activities that municipalities can engage in to build social capital.

7 Chart 4 - Norway

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E 50%

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A 30%

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0% Kristiansand Øvre Eiker Askim Herøy Vadsø

The Norwegian distribution across the five CLEAR components shows a very different set of profiles. Chart 4 summarises the findings from Norwegian municipalities. Two points stand out from this chart. First, as might be anticipated in a Nordic country (see also Finland, above), citizens are considered to have high levels of resources for political participation. All municipalities place some emphasis upon the ‘can do’ factor. Second, however, the perception of trust and reciprocity among Norwegian localities sits in direct contrast to those of the Dutch participants. The ‘like to’ feature of the framework is given considerable emphasis by all respondents, although the existence of strong and well supported civil society is more variable. To some extent, these high levels of trust may reflect the nature of Norwegian communities, especially those that are relatively remote from major conurbations. However, whatever the causes of this different perception, the point remains that it leads to potentially different policies towards participation and different priorities within the CLEAR framework.

Chart 5 - Slovakia

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80% L 70%

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E 50%

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A 30%

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R 10%

0% Vel'ké Kapušany Nesvady Závažná Poruba Kežmarok Bratislava

8 Chart 5 shows the CLEAR profile for Slovakia, a country with very different experiences of political participation. Despite these differences in experience, the chart shows a good distribution of emphasis across the five CLEAR components among all participating municipalities. However, it also shows some significant differences between localities. Probably the most striking feature of the chart (and the reports from which these figures are derived), however, is the relative difficulties that Slovakian localities face in developing a strong and vibrant civil society.

Chart 6 - Spain

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A 30%

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R 10%

0% Madrid Barcelona Málaga Córdoba Donostia - San Sebatián

Finally, chart 6 provides the profiles for the Spanish participants. Once again, there is a wide range of differences between the municipalities. However, a striking feature of the Spanish data is the range of ways in which all of the municipalities are actively seeking to extend the ways in which they engage citizens. This observation is especially true of Malaga, which recognises the limited resources which citizens in its localities have for engaging through conventional means, but is also true of all other municipalities as well.

The problem with all of these tables, of course, is that they disguise the contextual information which helps the reader to make sense of the observations in the full reports. Nevertheless, they do offer some interesting comparisons and trends.

Comparison by size

An alternative way of analysing the comparisons is to consider the effect of size on the way in which different profiles have emerged. Size of municipality, as measured by the population, is generally a good proxy for a range of other factors on which to compare participation. For example, larger municipalities are more likely to be significant urban centres and so on. It follows that population size may well have a significant affect upon the way CLEAR works in different localities. Small rural municipalities might be expected to be characterised by close knit communities with high levels of trust and well

9 developed (if often informal) methods for political engagement and self- government. The role of municipal authorities in creating a diverse range of participation initiatives and creating mechanisms for ensuring responsiveness is, arguably, limited in this context. In contrast, large urban centres are likely to be characterised by a variety of very different neighbourhoods and, consequently, might be expected to be fairly fragmented in terms of political engagement. While a significant population base will provide the space for a large number of non-governmental organisations to operate, there is also an important role for municipal authorities to play in both creating new opportunities for participation and in developing more responsive mechanisms. We can hypothesise, therefore, that population size would be an important variable in applying the CLEAR framework.

Chart 7 - Municipalities by size

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Largest ------Smallest

Chart 7 ranks the municipalities from largest to smallest, according to population size, using population information provided by the municipalities in their road test reports. The most striking observation from this chart is that there is no discernible trend that emerges: the hypothesis is not borne out in any obvious way by the profiles. Some of the smallest municipalities are just as likely to be giving emphasis to novel participation initiatives and promoting responsiveness as the largest municipalities. Moreover, there are no discernible trends in the middle of the table. The only exception is a general trend towards a smaller focus on the ‘enabled to’ component of the framework, as population size reduces. This observation is in keeping with the general hypothesis that decreasing population size is linked to a less formal framework for civil society activity.

10 The comparative analysis in perspective

The comparative analysis reveals a fairly wide level of variation between localities but very few significant trends that can be identified. Of course, one explanation for the absence of trends may well be that the subjective scores derived from the reports have misinterpreted the evidence in some way, and that those with more detailed contextual knowledge may well allocate the scores differently. This absence of trends is not necessarily a problem for the CLEAR framework. If individuals believe the distribution is wrong, then they are free to revise the profile according to their own assumptions. Regardless of how the profiles are revised, this redistribution does not invalidate the wider principle that there is no correct profile for municipalities. The CLEAR process has an heuristic rather than evaluative purpose.

At the very minimum, the wide variation revealed through this comparison is evidence in itself that the CLEAR tool has delivered very different results in each locality, confirming its value. Furthermore, by offering the evidence in comparative form it may well provoke participating municipalities to reflect further on why their locality differs from other with apparently similar characteristics. If municipalities rise to this challenge, the next step is for them to consider what approaches they need to adopt to achieve their aims. It is these policy options that the final part of this report now turns to.

11 Policy options and responses

If a CLEAR diagnosis reveals a profile that the locality is happy with, then there is no need for any policy response. However, it is our assumption that the process will reveal at least some areas where municipalities feel they should take some action to address gaps or limitations in what they currently observe. As Table 1 indicates, there are a range of responses that municipalities could make if their investigation using the CLEAR framework reveals “gaps” or areas of difficulty.

Table 1: Responding to investigative lessons from CLEAR

Key factor Policy Response

Can do Community development, training and development and practical support through the provision of community centres and resources targeted at those groups or communities that may need help to find their voice.

Like to Build a sense of community or neighbourliness. People have to feel part of a community to be comfortable with participation; so strategies of building social or community cohesion may be an important part in creating the right environment for participation

Enabled to Strong civic institutions can give the confidence to express their views. They may need to be monitored, challenged and managed so that they provide channels for the representation of a wide range of interests rather than a privileged position for a few. Investing in civic infrastructure and community networks, improving channels of communication is an important part of the policy agenda for municipalities committed to participation

Asked to Public participation schemes that are diverse and reflexive provide the best option in terms of making the ‘ask’ factor work. Different groups will require different forms of mobilisation. See Table Y for more details

Responded to A public policy system that shows a capacity to respond - through specific outcomes, ongoing learning and feedback

Of course, one of the main areas where municipalities might seek to change their profiles is in relation to their promotion and sponsorship of participation. These changes might involve extending the range of opportunities and initiatives or, more simply, changing the emphasis within them. Table 2 provides details of some of the many and diverse ways of asking the public their opinion.

12 Table 2: Different forms of ‘asked to’: applying CLEAR

Form Description Illustrative Case Web Resource Consultative Informs decision Public debate on the http://www.gmnation . innovations makers of citizens’ future of GM org.uk/ views through a technology in the UK combination of in 2001 methods to explore public opinion. Deliberative Enabling a cross- The British Columbia http://www.citizens methods section of citizens to Citizens’ Assembly in assembly.bc.ca have the time and Canada was opportunity to reflect established in 2004 on an issue by and over eleven gathering opinion and months, 160 were information in order given the task of to come to a reviewing the judgment about an province’s electoral issue or concern. system. Co-governance Arrangements aim to Participatory www.pgualc.org Mechanisms give citizens Budgeting started its significant influence existence as a form of during the process of engagement in Porto decision making, Alegre, Brazil in the particularly when it late 1980s but by 2004 comes to issues of it is estimated that distribution of public over 250 cities or spending and municipalities implementation practiced some practice. version of it Direct Referendums called Quite widely practised http://www . democracy by citizens that come in Switzerland and the iandrinstitute.org/ in two broad forms. United States Popular initiatives allow the recall of decision made by elected representatives. Citizens’ initiatives – allow citizens to set the agenda and put an issue up for public decision E-Democracy The use of The UK National www.edemocracy.gov.uk information and Project on local e- communication democracy has technology to give produced a wide range citizens new of tools for e- opportunities to participation aimed engage. specifically at helping local governments improve democratic engagement

13 As a self-diagnosis and heuristic tool, CLEAR provides a good first step to understanding the context of local participation in the round. The challenge for municipalities, and the Council of Europe more generally, is to build up a store of information and knowledge that can be exchanged so that the investigative lessons revealed by the application of CLEAR can be responded to and appropriate policy measures put in place. To conclude this report, therefore, we propose three fairly low cost mechanisms:

1. The central collection of a range of useful web sites containing details of participation schemes and information about developing participation strategies.

2. The development of a series of ‘Harvard-style’ case studies (about 15 pages long) that tell the narrative of particular municipalities and their interventions in the field of participation. To ensure the value of the case studies they should follow a standard format. They should provide a brief background account of the municipality and its area, an explanation of the problems and difficulties that they faced, a description of their policy response, a discussion of the successes and difficulties of that response and an overall assessment of what has been achieved and an email contact if the reader requires to ‘drill down’ further. The reports produced by each municipality for this road test, suitably edited, may provide a good starting point for these case studies.

3. The creation of a network of peer support based, and then extending beyond, the municipalities involved in the road test of the CLEAR framework. Peer channels for exchange could be initially within a country and then if appropriate extended on an international basis.

Some of these activities could be co-ordinated by the Council of Europe. Others could be underwritten and supported by national or regional governments or national or regional associations of local government. In this way, CLEAR could become of relevance to all municipalities across Europe.

14 Appendix 1 – Scores by Municipality

FINLAND

Tampere

Characteristics Per cent C Population and socio economic profile identified 25 Citizens have access for political participation, but time is a restriction Citizens have skills for participating L People trust each other and the municipality 29 People are responsible to the area where they live People are helpful People have similar values/priorities for developing the area where they live Low sense of people being excluded Low sense of some group voices being more legitimate than others E Wide range of voluntary organisations 14 Political parties are the most influential There are umbrella organisations The municipality supports the voluntary sector A There are more than three forms to engage citizens in decision making 18 Wide use of the Internet to engage citizens Participation activities take place in official & unofficial venues Constant renewal forms to engage different social groups Statistical data have priority to take decisions R The local press is used to communicate decisions 14 Official bodies make final municipal decision based on citizen surveys/consultations Citizen programmes are focused on children and youth groups Officers are trained