Logode Jong, M. (1999). Survival of the institutionally fittest concepts.
Journal of Memetics - Evolutionary Models of Information Transmission, 3.
http://cfpm.org/jom-emit/1999/vol3/de_jong_m.html


Survival of the institutionally fittest concepts

Martin de Jong
Faculty of Technology, Policy and Management
Delft University of Technology
Jaffalaan 5, 2628 BX Delft, The Netherlands
Tel. +31 15 278 3433 Fax. +31 15 278 6439
martinj@sepa.tudelft.nl
Abstract
1 - Introduction
2 - Institutional structures as information filters
3 - Institutional structures, behavioural bias and conceptual bias
3.1 - Four types of institutions
4 - Evolution of conceptual bias in institutional structures
4.1 - The complete replacement of the conceptual framework by another (paradigm shift)
4.2 - A partial change in the conceptual framework (slight mutation)
5 - Institutional selection and fit concepts
5.1 - The creation of a variation of concepts
5.2 - The selection of concepts
6 - Conceptual learning in political theory
6.1 - Hall's work: Social learning and its three orders
6.2 - Sabatier's work: advocacy coalitions holding incompatible belief systems
6.3 - Hajer's work: discourse coalitions producing potentially compatible story lines
6.4 - Similarities, differences and surplus value
Acknowledgements
Notes
References


Abstract

Certain arguments generated by political and administrative actors find their way to tangible policy actions, others do not. Some information is embraced by actors in institutional systems, whereas other arguments and facts can be ignored with impunity. Apparently, institutional structures constitute a persistent tendency to favour particular arguments at the cost of others. In decision making processes, i.e. processes during which a selection is to be made among various alternative policy options, institutional structures, consisting of existing decision rules and practices, operate as an information filter creating a conceptual bias.

 This article spots the issue of political decision making from an evolutionary and memetics perspective, employing terms such as variation and selection, mutation and replication, information transmission and fit concepts. With the aid of the evolutionary theoretical framework, the mechanism that decides why and when certain concepts are deemed fruitful and others die is pinpointed. Examples from the field of investments in transport infrastructure in England are used to clarify the line of thought. At the end, the evolutionary perspective derived from biology is compared to well-known authors in political science to see if complementary ground can be found.


1 Introduction

Certain arguments generated by political and administrative actors find their way to tangible policy actions, others do not. Some information is embraced by actors in institutional systems, whereas other arguments and facts can be ignored with impunity. Apparently, existing decision rules and practices constitute a persistent tendency to favour particular arguments at the cost of others. Schattschneider (1965), a well-known political scientist, dubbed the implicit or explicit favouring of certain actors and subjects and the waiving of others mobilisation of bias; a bias built into the institutional structure addressing the finite attention of powerful actors to certain policy-matters at the expense of others.

 This article introduces an additional element to mobilisation of bias: concepts. Decisions are often made with the help of conceptual models indicating which information is relevant and to be searched and which is not to be paid any attention to. The political agenda not only favours specific actors and policy-issues, but also the way they are addressed. Argumentative practices follow the bias built into these conceptual decision models and thereby determine the criteria on which policy-decisions are based. The models frame both importance and interpretation of concepts, conceptions, reasonings and data. Some arguments are generated because the institutional structure evokes them, others never even see the light of day. Some arguments are selected in and transformed into actual decisions, others are weeded out before even reaching the finishing post. Argumentative practices that have been institutionalised are part of the `dominant institutional complex' and guide the way to the gathering of decisionally relevant information. Reasonings and data along this line are successful because they fit into the conceptual frame embraced by actors possessing the prevalent policy instruments (funds, properties, legal competences). Arguments which are either not produced, which remain latent or which are discussed but ignored when it comes to decision-making do not comply with the criteria defined by those `in power' in the institutional system. They are relegated to the `recessive complex', a discourse remaining mainly under the surface. Apparently, we are dealing with a selective mechanism for concepts here: the present institutional structure consists of existing political rules and argumentative practices that act as an information filter for incoming arguments and data.

In this article, the mobilisation process described above is reframed in evolutionary terminology. I claim that current theories using an institutional framework can be enriched by observing them as processes in which a certain variation of concepts is created and further on selected by the institutional structure, which acts as a selective environment, as a filter concepts have to pass before having any material consequences. If we consider individual concepts as single memes (Price & Shaw 1996), conceptual frameworks as memeplexes and information filters consisting of selection criteria as memetic filters as described by Dennett (1995), we may bring political science and memetics, the conceptual version of biological evolutionary theory, much closer to each other. Observing institutional development, exchange of argumentation and actor behaviour as processes of evolutionary change adds an element of dynamics to political analysis that in my view is often overlooked. Evolutionary theory is by its nature engaged in describing and explaining mechanisms of mutation, change and development and is therefore a bride bringing in a very attractive dowry: a fruitful analogy. [note 1]

Memetics, on the other hand, being a theoretically rich and promising framework badly needs empirical filling. This article aims to provide this type of evidence by linking memetics to conceptual change in political decision making.

In section 2, `Institutional structures as information filters', I will first present the idea of information filters as it was coined by Dennett (1995). In a situation of information abundance, a framework of rules evolves to base selections on. This very same mechanism works in both the selection of good poetry and the choice between policy alternatives, as will be shown with an example derived from English transport policy.

As information filters have the form of institutional structures when policy-making is concerned, we will then dive into the definition and description of institutions. Section 3, `Institutional structures, behavioural bias and conceptual bias', will highlight the distinction between behavioural and conceptual institutions and their interplay in the institutional structure as a whole. This look at institutional structures synthesises current insights. From the literature we know that formal and informal power structures can exclude certain actors from the policy-process. We also know that the use of a dominant terminology may prevent certain ideas or certain notions from being aired. Section 3 combines these two interdependent aspects and shows how their interplay influences the gathering and selection of information and alternatives.

Section 4, `Evolution of conceptual bias in institutional structures', gives some examples of institutional change. Particular concepts which first were sieved out by the filter later on came to be embraced by powerful actors and incorporated in the newly adapted institutional complex. This can happen because initially recessive concepts sometimes keep lingering around and `wait' for some later opportunity. Dominant actors usually have self-interested motives for such a sudden volte face.

`Institutional selection and fit concepts', the fifth section, recapitulates the evolutionary insights in this article and tries to identify the essentials of a `fit concept', a concept that finds its way through the filter and is thus selected in. What mechanisms decide whether a concept becomes dominant in an institutional structure?

 The concluding section 6 investigates how the approach propagated here relates to other political theories about learning as developed by Sabatier (1987) , Sabatier & Jenkins-Smith (1993), Hajer (1995) and Hall (1993).


2 Institutional structures as information filters

In modern evolutionary biology organisms' genes or geneplexes are considered the unities which are replicated from generation to generation. Organisms are built up following the construction plan contained in their genes and after procreation copy this genetic material to their offspring. They are therefore the carriers of genetic information. Their role is not restricted to that of being only passive vehicles however. Among different organisms or populations of organisms survival and procreation rates differ. They live in a natural environment that allows certain exemplars to survive and prosper, while others fade away or starve. This natural environment leads some (populations of) organisms to survive and spread where others do not. It is a selection mechanism in the sense that only the genetic material of the successful is replicated unto following generations. The differential genetic replication rates between successful and unsuccessful lineages of carriers result in genetic evolution across generations.

Recently, this line of evolutionary thought has been enlarged to the social world as well. Just as we can observe a replication process of genetic information in the world of biology, there is a replication process of memetic information in the world of thought and learning. Ideas (`memes') living in the one actor's brain can by means of communication be replicated to other brains, and the more this occurs to a certain idea the higher is its replication rate and the greater is its success. A very intriguing thought. But if, according to this analogy, memetic information replaces genetic information and if we see an actor's brains as the carriers, what can we say about the natural selection environment? What ruthless selective filter sieves out the unsuccessful ideas? Dennett (1993) gives an impression of what a memetic filter looks like. Here is an extensive quote telling how `good poems' in an electronic network may be traced in a vast pool of poetic dump produced by both brilliant and mediocre poets.

John McCarthy, one of the founders of Artificial Intelligence (...) once suggested to a humanist audience that electronic-mail networks could revolutionize the ecology of the poet. Only a handful of poets can make their living by selling poems, McCarthy noted, because poetry books are slender, expensive volumes purchased by very few individuals and libraries. But imagine what would happen if poets could put their poems on an international network, where anybody could read them or copy them for a penny, electronically transferred to the poet's royalty account. This could provide a steady source of income for many poets, he surmised. Quite independently of any aesthetic objections poets and poetry-lovers might have to poems embodied in electronic media, the obvious counter hypothesis arises from population memetics. If such a network were established, no poetry-lover would be willing to wade through thousands of electronic files filled with doggerel, looking for the good poems; there would be a niche created for various memes for poetry filters. One could subscribe, for a few pennies, to an editorial service that scanned the infosphere for good poems. Different services, with different critical standards, would flourish, as would services that screened, collected, formatted and presented the works of the best poets in slender electronic volumes which only a few would purchase. In other words, the memes for editing and criticism will find niches in any environment in the infosphere; they flourish because of the short supply and limited capacity of minds, whatever the transmission media between minds. Do you doubt this prediction? If so, I'd like to discuss framing a suitable wager with you. Here once again, as we have seen so often in evolutionary thinking, explanation proceeds by an assumption that the processes -whatever their media, and whatever the contingent zigs and zags of their particular trajectories- will home in on the forced moves and other Good Tricks in the relevant space.

The structure of filters is complex and quick to respond to new challenges, but of course it doesn't always `work'. The competition among memes to break through the filters leads to an `arms race'of ploy and counterploy, with ever more elaborate `advertising' raised against ever more layers of selective filters (Dennett 1993: 350).

The quality selection devices Dennett speaks of consist of a framework of search rules or heuristics. Poems meeting certain standards in terms of poet's name and reputation, employed vocabulary, length, subject, rhyme or melody and conformity to style characteristics will flow through, while lousy amateur near-sonnets or unconventional absurdist products by unknown artists won't find their way out of the electronic maze. In the end, the brain of the actor using the search device will only copy the ideas contained in the selected poems: the filter did its work.

Now suppose civil servants working at the English Department of Transport have to decide on the future of the national transport network. They are responsible for the funding of projects, programmes or bids other actors submit to them. They do not have the financial means to approve of them all, so they have to make a warranted selection among them. This leaves them no other choice but to establish criteria by which they can determine what information is relevant. If they need to justify the quality of their selection they cannot escape developing rules telling which projects can be considered valuable and which cannot.

To cope with information overload the Department of Transport (DoT) in London has developed a cost-benefit analysis (COBA) to evaluate proposals submitted by local governments. As local governments can hardly levy any financial means by themselves, they rely on central funds for the realisation of infrastruture projects. Well aware of this situation, DoT conscientiously applies this COBA model and has promulgated a paper explaining the functioning of the priority-setting method enumerating criteria by which the desirability of infrastructure projects can be determined. It pays specific attention to the following aspects (DoT 1989, May 1991, DoT 1994, Steer 1995, De Jong 1999):

Just like the poetry filters select poetic products that meet certain standards, COBA's criteria weed out project bids with low scores on the abovementioned criteria. Local governments' financial claims should be substantiated by a summing up of information on all of these aspects and preferably expressing the total value of projects in the monetary unit: profitability in hard pounds. There clearly is a bias in COBA. It explicitly excludes user benefits from consideration, claiming that they will be discounted in the market price. On the other hand, the rise in market value in certain areas generated by new infrastructure should be included in the calculation. These arguments set public transport at a significant disadvantage (May 1991). Benefits and costs are only calculated for criteria summed up in the method of appraisal and their outcoming ratios reflect the conceptual bias.

To put it differently, DoT desires rather detailed information from local governments before they can get the money they need. To make them understand what kind of data they should deliver, it proposes an informational format stipulating the aspects they should pay attention to and how they are expected to add them all up. Using the format is not compulsory; if they wish to calculate profitability in their own way, they are free to do so. But when they submit their proposal in London, at least they are abreast of the criteria they will be judged on. Dennett's poets are in exactly the same position, they are still allowed to put experimental or amateur work on the web, but their chances for selection are minimised by the format of the filter. They may still avoid treating love and sex as the primary issues in their work, but they risk missing out lots of readers.

Rigorous and uncompromising application places dissident local authorities in a difficult position. Information they possibly attach value to will not make it through the COBA filter. As a result, their pet projects will not receive the required funding.

How do local governments generally react in a competitive environment where their local brothers are not friends but foes? They adapt to London standards or die. Authorities that have their bids sanctioned underscore the profitability of their projects, introduce an impressive list of well-known and less well-known banks, project developers and consultancy firms whose actual contribution is sometimes doubtful, ask for new roads and by-passes around the city-centre and invest only in `shinier kinds' of public transport such as tramways leading to the crntral areas. Furthermore, as DoT mentions in its `S56-circular', it is highly irrational to extensively calculate environmental benefits which are not or not easily quantifiable. On the other hand, it is highly rational to have good contacts with the Government Offices, deconcentrated national offices in the regions. They know all the ins and outs of London decision-making and can give good advice on how and when to plug bids in and what terminology is appreciated in the capital. It is precisely this compliance which begets both success for the money-claimants and materialisation of the COBA-worldview for the money-provider, a perhaps even bigger success. As one can easily understand, the effect a poetry filter has on individual poets, at least those desiring to be read, will be no different. They too will cunningly market their products and start treating each other as rivals in the infospace. [note 2]

To conclude, the complex of rules indicating what criteria or standards poems or transport investment bids should meet to be in the selection and what actor(s) have a say on this matter in policy-making is called `institutional structure'.


3 Institutional structures, behavioural bias and conceptual bias

An enormous number of volumes from different authors and various scientific disciplines have appeared on `institutions', but little common ground has been found. Here, we follow Simon (1982, 1992), North (1981, 1990), March and Olsen (1976, 1989) and Hall (1993).

Institutions are rules which enable actors to cope with uncertainty when making decisions. [note 3]

One can say that all complex choices actors need to make require an amount of information not directly available. It is not always feasible to collect this information; it is either too expensive, too time-consuming or too annoying. Nor is it always necessary; knowledge gathered in the past has often been recorded in terms of usual practices, norms of conduct, traditions or standard operating procedures. The decision rules implied in these institutions, `correct' or not, are readily available and may save actors hugely in terms of transactions costs. If an actor has a decision model based on experience, it does not make sense to put it in doubt every time it is used: rules are very often functional and reassuring. We can clearly see the parallel with the filter mentioned in preceding section.

For the purpose of this article, showing how mobilisation of conceptual bias works, the above mentioned definition of institutions is still too general. I would therefore like to make a double distinction resulting in a two by two matrix of types of institutions.

  1. Institutions can be either formal or informal. Formal institutions are legal-verbal procedures reflecting the official `rules of the game'. Informal institutions are the non-verbal, non-official current practices developed by players during the game.
  2. Institutions can be either conceptual or behavioural. Conceptual institutions are rules indicating how actors should think about an impending choice; they delimit the interpretative freedom. Behavioural institutions are rules that decide how actors should or should not act; they restrict the interactive freedom. [note 4]

3.1 Four types of institutions

Type of institution Formal Informal
Behavioural; rules for
appropriate interaction
Procedures,
arrangements
Behavioural codes,
Norms of conduct
Conceptual; rules for
appropraite interpretation
Decision rules,
standards, criteria
Approaches, visions,
conceptions, frames

The ensemble of these various rules in a specific (policy) area is called the institutional complex or institutional structure. Arguments brought in by different actors are `filtered' by this complex, and only those fitting in with the dominant complex embraced by the currently most powerful actors acquire influence on the `real' decision making. It seems that concepts are `fit' when they `fit in'. Though this is true to large extent, it is also highly tautological. If concepts did not survive, they apparently didn't fit in. Fortunately, this is not totally true. Some concepts do not conform to the institutional standards at first, but do reach institutional hegemony after fierce conceptual struggle. Other concepts should be fit considering their possession of the properties demanded by the institutional environment, and yet don't make it if competition is too strong. [note 5]

One important point still begs clarification. I have mentioned that institutional structures have a bias in favour of certain arguments and facts at the expense of others. I have also written that institutional complexes function as a selective environment for concepts introduced by actors. Does this mean that `structures' are the same as `complexes' and that `arguments and facts' equal `concepts'?

 The answer to the first question is yes, more or less. The only slight difference is that the word `complex' sounds more evolutionary and more open to the conceptual side of choice-making than `structure', which has a static ring to it. Nevertheless, the terms are interchangeable here.

The answer to the second question is less straightforward. So far I have used the terms concepts, conceptions, arguments, facts and criteria rather loosely, as is unfortunately quite often also the case in how the term `meme' is generally used. This conceptual informality will end from now on. Concepts are singular words having a particular significance. They can be seen as the smallest thinkable entity which can be replicated. Conceptions or conceptual systems are a totality, a combination of concepts forming a meaningful frame. Arguments are assumed causal connections between concepts, which provide insight into a specific question or problem. Giving an argument actually means picking out two or a few concepts from a conceptual system which have a relation with each other to address a particular issue. If a specific argument is widely accepted as being the correct way to address a specific issue at all times, it becomes a criterion: the argument is formalised. Last but not least, facts are events or data that are shown to prove particular arguments right or wrong. They can be either qualitative or quantitative, but are only meaningful in the context of the argument for which they are used.

Toulmin (1972) wrote a wise phrase saying that concepts are micro-institutions, and institutions are macro-concepts. Disregarding the fact that institutional complexes not only consist of conceptual elements, but of behavioural elements as well, it helps to understand how institutional complexes composed of conceptual notions generally select like-minded and related concepts and occasionally incorporate new concepts within this system, which then become micro-institutions. As a result, institutional change occurs. Which micro-institutions will be part of the macro-complex and when they will obtain their place depends mainly on the relations contained in the behavioural institutions. Dominant actors have their interests and are supportive of concepts that promote these interests.


4 Evolution of conceptual bias in institutional structures

The preceding sections have demonstrated that institutional structures work as filters that select certain incoming concepts in and weed others out. But the relationship between concepts and institutions can also be approached from a more dynamic angle: how previously ignored concepts become institutionalised themselves, succeeding thereby in changing argumentative links in the till then dominant institutional complex. This does not happen all that often, however; it requires political momentum. Big changes only come to be when the rigid existing complex can no longer deal with societal problems, such as abnormal congestion or exuberant pollution (Krasner 1984, 1988). Such situations put the dominant complex under strain and can lead to institutional evolution via two different paths which I will describe underneath:

4.1 The complete replacement of the conceptual framework by another (paradigm shift)

In this case, the dominant actor(s) is/are confronted with increased resistance from recessive actors that no longer accept its/their conceptual and behavioural hegemony and challenge the existing the institutional structure as a whole. Following the increased behavioural strength of the recessive actors, a fierce conceptual struggle begins in which the dominant actor(s) also loses the conceptual initiative and finally has to give way.

In the South East of England counties and districts were confronted with DoT's fairly centralist attitude to infrastructure planning, as described in the section 2. Feeling frustrated and noting they were continually by-passed and competed by each other while London actively exploited their weak positions, they decided to get in touch with one another more intensely. Some local governments realised they had good roads and mediocre public transport and for others the situation was the other way around. Acknowledging their interdependence and regrouping together they were able to restructure the negotiations with London along regional lines (DoE/SERO 1994, SERPLAN 1994, Steer 1995). Consequently, the behavioural institutions started to change. After an `initiation process' in which they had to get used to cooperating with their former rivals, they established `package bids' with proposals for funds aimed at the whole region. They challenged London's hegemony by speaking with one voice. Besides they found active conceptual support from the London and South East Regional Planning Conference, a successful advisory organisation funded by all local governments in the region, that catalysed and facilitated mutual adaptation. It had developed knowledge in spatial planning and environmental costs and has usually been ahead in conceptual innovation. As DoT sensed that vital information was no longer spontaneously provided from local authorities to itself, but only to other regional authorities, it accepted the London and South East Regional Planning Conference as a regular institutional body. In this way the package bid approach replaced the application of COBA.

Tthe coherence of thought implied by a package of measures does not lend itself well to a scheme-by-scheme appraisal, which is the established basis on which funding decisions are made. Funding agencies will no doubt continue to ask for a cost-benefit assessment of individual projects, but these appraisals do not answer the question inevitably posed by the package approach: what contribution to the overall strategy does this particular scheme or policy make? The aims of the overall strategy are not capable of expression in terms of quantified benefit-cost ratio targets. It follows that at the scheme, as well as strategy, level attempts will have to be made to develop new appraisal systems (Steer 1995: 204).

The basis for this investment approach was the `Integrated Transport Studies' in which traffic trends from the past were not simply extrapolated to the future, but various effects of traffic growth were correlated with dynamic patterns of spatial evolution. In this approach the environmental and spatial effect in the region came much more to the fore, as well as a more holistic view of traffic streams. The change in the behavioural institutions, the stronger position of regional governments and their private representative, led to the institutionalisation of a wholly new conceptual framework. As a consequence the old institutional complex was replaced by a new approach. DoT did try and continue to judge the package bids with the help of COBA (in effect the two `filters' temporarily co-existed), but it gradually had to give way. In the end, the project bids for the South East were submitted to a completely changed filter.

4.2 A partial change in the conceptual framework (slight mutation)

In this less revolutionary case, dominant actors anticipate the weakening of their behavioural position and prevent it by allowing recessive actors to have some more influence by accepting a few of their recessive concepts. They integrate them into the dominant institutional structure to placate the recessive actors without having to give up the dominant paradigm. In this case, dominant actors are more forwardlooking and do not have to go through the painful process of giving up funds, political positions or legal competences. They only have to consent to some conceptual adaptations in the institutional complex to accommodate and placate dissident actors.

DoT in London has for some decades applied a variant of COBA for the assessment of trunk roads and motorways. Until recently, the model utilised a purely demand based philosophy: if road congestion exceeded a certain threshold, more asphalt had to be constructed. The Transport Research Laboratory, a research organisation outside the centre of the decision making network, had been criticising the demand based line of thought since the beginning of the 1980s. They promoted the idea of so-called `induced traffic': a higher supply of good infrastructure creates its own increased demand for transport. For this reason, when DoT had more roads built, automatically new and till then latent car drivers would suddenly appear on the road network. The conventional COBA model did not take such phenomena into account and therefore arranged for the acccommodation of traffic it continually generated itself. Even though many observers outside the Transport Research Laboratory were aware of this phenomenon, at that time the automobile lobby was too strong to push through any new concepts. The Special Advisory Commission on Trunk Roads Assessment (SACTRA), a high status advisory board for counselling on new motorway projects agreed, but felt the time was not yet right for a fundamental change in orientation. DoT also had many investment programmes running, based on the existing model.

But by the mid nineties, popular support for the construction of more roads had declined tremendously. Environmental groups antagonised more strongly than ever against new inroads on British scenery. The conservative government decided to drastically curtail the budget for infrastructure planning and the accompanying taxes in order to increase its chances to win the elections. DoT was forced to adapt its ways and SACTRA issued an innovative report telling the nation that every new supply of infrastructure did indeed generate its own demand. DoT now voluntarily accepted the ideas in this official advice and redesigned COBA in line with the new more sobre philosophy and had all running road projects recalculated and reweighed by SACTRA. Forty-nine formerly approved investments could be scrapped and cancelled. In this second case, the dominant actor was able to prevent a dramatic change in the institutional structure by allowing some conceptual mutation, but clearly within the existing conceptual framework (DoT 1994, CBI 1995).


5 Institutional selection and fit concepts

Considering the exchange of arguments as concepts waging a struggle for survival in institutional complexes gives us some valuable insights in the dynamics of decision making. But there is a philosophical problem here. Do concepts, mere words that is, actually struggle? Aren't concepts only puppets on strains, used as manipulative tools by humans or actors to serve their interests? They do not have a will of their own, do they?

In biology, there is an equivalent discussion concerning the `levels of selection' (Brandon 1988). Leading theorists in evolutionary theory do not agree among themselves about these levels of selection. Some say that selfish genes really fight for their own subsistence and that they are the ones that live through generations. In that case individual organisms are no more than helpless vehicles that replicate invisible information codes vital to evolution (Dawkins 1976). In the social science analogy, this would imply that actors are only the means through which concepts are transferred and that real selection is `executed' only on concepts. Others claim that organisms are the ones that matter when it comes to the weeding out process, not genes. As a result, the transplantation of genetical material depends on the survival and reproduction of their carriers. Organisms are not simple vehicles, but acting and interacting entities that during their lives `determine' whether the genes according to which codes they are built deserve a future (Sober 1984). For the process of conceptual evolution, this would mean that the success of actor fitness and behaviour make a difference. They are active carriers of ideas, not passive vehicles, so in the end the survival of ideas depends on them. The last group of theorists focuses on whole populations of organisms. Considering a much larger time span and the success of species, subspecies or geographically dispersed groups within a species, these theorists generally conclude that populations that are bigger or have a greater variation in their total `geneplex' are also fitter in the long run. Besides, individual organisms may have a strong physical constitution but may lack the advantages of a protective social group (Brandon 1988). [note 6]

As all lines of thought have a point, the decision on what the level of selection is cannot be definitively answered. Hull (1988) found a way out of this dilemma by introducing the difference between interactors and replicators. He defines them as follows:

replicator: an entity that passes on its structure largely intact in successive replications.

interactor: an entity that interacts as a cohesive whole with its environment in such a way that this interaction causes replication to be differential.

With the aid of these terms selection can be charaterized succinctly as follows:

selection: a process in which the differential extinction and proliferation of interactors cause the differential perpetuation of the relevant replicators.

Replicators and interactors are the entities that function in selection processes. Some general term is also needed for the entities that result from successive replications (Hull 1988: 408-409).

Now jumping back to the world of concepts and actors, we can see that actors interact with their environment causing concepts and conceptual systems to be replicated differentially. Concepts only tied to `unfit', i.e. politically weak, actors are also unfit and have a greater chance of being weeded out. For concepts used by fit actors the opposite goes: they are often selected in. The differential success of actors to spread their concepts produces an outcome known as conceptual evolution.

At the outset of this article, we saw that concepts went through an institutional structure or `filter' before being selected or not. According to Hull's definition, (inter)actors operate in an environment that causes (conceptual) replication to be differential. In the case of biological evolution it is the natural environment or ecology that causes the replication of genetic information to be differential. When speaking of conceptual evolution, it is the institutional structure that makes the procreation of some concepts more successful than the spreading of others.

If, following Toulmin (1972), we make a distinction between the creation of a variation of concepts (A) and their selection process (B), we acquire a full picture of the mechanisms behind conceptual evolution.

5.1 The creation of a variation of concepts

In the first place, actors must produce and utilise concepts before they are taken to their selective arena or filter. Concepts spread through replication from one actor to another. When concepts are replicated, small mutations or recombinations take place once in a while: their meaning changes, they acquire an extra connotation or they are applied to a different domain than previously. In other cases, whole new words are coined or invented. Conceptual mutation creates a greater variation of ideas to arise. In itself the replication of a concept from one actor to another only generates conceptual change in the `brain' of the receiving actor. But it may also provoke changes in this actor's perceptions and preferences and lead to different judgements of policies. This latter phenomenon leads them to act differently, carrying the germ of behavioural change.

5.2 The selection of concepts

The institutional complex reflects the dominant behavioural and conceptual practices developed from the past unto now and serves as a filter to the new incoming variation of concepts brought forward by actors. The behavioural institutions structure who is/are allowed to come in and perform what function with what means, the conceptual institutions are a conceptual system structuring what concepts and arguments are deemed meaningful by dominant actors. It contains the criteria applied to the selection of newly introduced concepts at a particular moment, but this too may evolve. If a specific concept has been replicated sufficiently to affect the wishes of dominant actors within the selective arena, it may institutionalise and become part of this filter. [note 7]

If the existence of institutional structures can be established fairly easily by describing a system's written and oral rules of decision making, circumscribing what makes for the fitness of a concept is less self-evident. In the preceding sections, we saw that concepts in conformity with the criteria in the dominant complex are rather more successful than dissident ideas. Therefore, if dominant actors have developed and endorsed criteria for investment proposals demanding strong private participation and approve of schemes to promote renewal of run down innercity areas, investment proposals framed in those terms clearly have a higher probability to be selected than otherwise. But fitness is a stochastic and plural quality. It is stochastic in the sense that potentially viable concepts can fail for other reasons. They may enter the selection arena when other even stronger concepts happen to arrive as well or the actor presenting them may be out of grace. Fitness is plural or multiple in the sense that it has many sides to it. It is related to conceptual criteria as the ones just mentioned, but it is also related to behavioural criteria such as consulting friendly representatives from dominant actors for some good advice or allying with friend actors to reinforce one's position. However, generally it is the concepts' usefulness in the eyes of actors that makes them viable. Hull (1988) spoke of conceptual inclusive fitness: concepts are mainly replicated because of their ability to make individual actors understand and solve problems. In that sense they should be (1) applicable to a wide range of phenomena and (2) provide deep insight in these problems. Also, when concepts have a structuring effect on other concepts, they will obtain a vital role in the web of a conceptual system or paradigm and attract or catch many other concepts in their webs. Concepts like `the market', `flexibility' or `paradigm' seem to have these characteristics. If a sufficiently large number of actors share the opinion that a concept is needed or useful, one can say that it is `fit'. This situation occurs in the two types of situations mentioned in the preceding section: namely (1) when a concept has already been institutionalised, or (2) when the current institutional structure is threatened or in crisis and actors recognise that the till then recessively lingering concept fills the problem-solving gap all concepts in the old complex were unable to fill.

As we saw in section 2, in some cases dependent actors have to adapt to the concepts imposed by more dominant ones. And in other cases, the ones in section 4, a whole group of not too strong actors may once in a while succeed in forcing dominant ones to retreat and by and by push in a wholly new conceptual system, realising a `paradigm shift' so to say. Often the combination of many fitness aspects together augments probability of survival, but some kind of `chance' may always get in the way.

 But increasing probabilities to be successful is not the same as predicting with certainty. The evolutionary perspective may be helpful in understanding the way conceptual bias is mobilised, but framing decision making in terms of conceptual fitness does not help us to automatically forecast the success of investment proposals, even though we know they are verbally framed. That would have been too beautiful anyway. In the concluding section, the evolutionary framework presented in this article will be compared to the lines of thought by leading political theorists to see if some common or complementary ground can be found.


6 Conceptual learning in political theory

Even though `conceptual evolution' is as far as I know a new term in the field of political science, this does not mean that attention to processes of policy learning has been absent. On the contrary, theorists such as Hall (1993), Sabatier (1988, 1993) and Hajer (1995) have tried to describe social or political learning in terms of `social learning' and `paradigm shifts' (Hall), `advocacy coalitions' and `belief systems' (Sabatier) and `discourse coalitions' and `story lines' (Hajer). After a short description of their central ideas, I will point out their similarities and differences with the line of thought in this article. [note 8]

6.1 Hall's work: Social learning and its three orders

Hall describes the process of policy learning as the acquisition of new information on the working of current policy measures and goals and the resulting changes in these measures and goals due to this new experience. He then disaggregates learning into three different types or `orders':

  1. First order learning concerns only adaptations in precise settings by which policy instruments and techniques are put to use.
  2. Second order learning involves the types of policy instruments which are employed in the policy field and how possible combinations of these instruments are made.
  3. Third order learning leads to a complete change in the overarching hierarchy of goals that guide policy in a particular field, in effect being a `Gestalt change' or `paradigm shift'.

Hall has rather specified ideas about this Gestalt or paradigm guiding public policymaking, and they bear a strong resemblance to the framework in this article:

(...) policies are made within some system of ideas and standards which is comprehensible and plausible to the actors involved. More precisely, policy makers customarily work within a framework of ideas and standards that specifies not only the goals of policy and the kind of instruments that can be used to attain them, but also the very nature of the problems they are meant to be addressing. Like a Gestalt, this framework is embedded in the very terminology through which policymakers communicate about their work, and it is influential precisely becasue so much of it is taken for granted and unamenable to scrutiny as a whole. I am going to call this interpretive framework a policy paradigm (Hall 1993: 279).

Hall pays attention to different levels of learning, his terminology is slightly different and in this article the emphasis on the process of conceptual evolution is more important, but there clearly seems to be some common ground.
 
 

6.2 Sabatier's work: advocacy coalitions holding incompatible belief systems

Sabatier claims that at the heart of certain policy debates, between groups of actors there is not just a clash of ad hoc arguments, but an incompatibility of deeper lying belief systems consisting of diverging images of man, society and administration. He explicitly bases his term `belief systems' on Kuhn's scientific `paradigms'. The prime example of a belief system struggle for which it is impossible to find definitive compromises, is the debate between economy and ecology. The materialist, efficiency assumptions on which the one, and the post-materialist sustainability assumptions on which the second thrives cannot be unisoned at an abstract level. For this reason, both will basically remain distinct belief systems that conflicting groups of actors align around.

Incompatibility in the abstract, however, does not imply that at the level of more specific policy measures, concessions from both sides are impossible. The only manner to make decisions robust enough to be effective is either to push through one of both approaches by forming a coalition of actors strong enough to take control of all necessary policy instruments or to build compromises between both coalitions. The gap between a belief system and concrete measures can be bridged by translating the central assumptions to more peripheral elaborations. In this way, choices that boost the economy may be prevented from harming the environment or decisions can be made that reduce pernicious emissions while at the same time benefiting production processes. Pollution prevention may pay, as ecological modernism has it. By incorporating peripheral ideas from the enemy belief system in their own framework, an advocacy coalition can learn.

To conclude, agreement in the abstract about belief systems will for ever remain impossible, but ephemeral junctions between them are not. As a result, the latter aspect keeps the policy process going and learning, while the first keeps on producing struggles.

6.3 Hajer's work: discourse coalitions producing potentially compatible story lines

Hajer finds much of value in Sabatier's approach, but he emphatically rejects the idea that any core belief systems exist. Following a more post-modernist line, he explains how policies consist of narratives composed of competing story lines. Different actors employ different narratives and once they have come to a textual agreement, one may say that a new, possibly innovative discourse has institutionalised. As there are no core assumptions coalitions of actors can be pinned down on, there might very well be diverging discourses, but they are not by necessity incompatible. Newly created and creative story lines introduced to the ongoing debate can displace old ones if they have a high potential of being picked up by others. However, as in Sabatier's case, some actors are more equal than others. When this line of reasoning is translated to discourses, it appears that some discourse coalitions are more potent than others. Hajer defines discourse coalitions as `assemblages of ideas, concepts and categories through which meaning is given to phenomena'. Those `in power' having their say on what should financially or physically happen determine largely which discourses overpower others and in what manner.

To conclude, as story lines instead of core assumptions decide on the orientation of political debates there is no essential incompatibility between different approaches; they are not immobile, but evolve. No essence can be established in any narrative. Still, some discourses win, while others lose, depending on institutional structures. By inventing new attractive story lines, losers might recover their lost ground.

6.4 Similarities, differences and surplus value

Apart from certain evident conflicting points between the various approaches to policy learning, there are two remarkable points of agreement.

Firstly, they all implicitly or explicitly refer to lines of thought developed in the philosophy of science, mainly Kuhn's paradigms (1962). Hajer and this author are more hesitant in following the paradigm approach, as the incompatibility of (policy) paradigms is not self-evident or probably even wrong. Words or concepts may have no essential meaning, but adapt their significance when being referred to other words or concepts, as Toulmin (1972) and Hull (1988) have clearly shown. But still, the theories of political learning all originate to an important extent in the philosophy of science.

Secondly, all authors consider both aspects of political power and the exchange of ideas as crucial to policy learning. In fact, it is precisely their intertwinement which lies at its basis. Or, as Hall beautifully summarises:

Nevertheless, the approach in this article has been different from or complementary to the others in two respects. It has highlighted the role of the existing institutional structure at a particular moment in time in filtering the incoming new information. It has also focussed on the survival chances of new information by taking notice of `fitness aspects'. Both elements shed some light on the mechanisms behind conceptual evolution and may provide additional insights as compared to those already existing. On the other hand, a theory looking mainly at concepts and much less on policy instruments and techniques may be too strongly verbally oriented. In that sense, Hall's framework can add to the insights developed here.


Acknowledgements

This paper was written after intense and intensive discussion with my colleague and friend Hans Cees Speel. I mainly owe him for his explanations of the working of `selective environments' in biology and the `science of memetics'. Frans van Waarden, Joop Koppenjan and Bert Enserink also gave valuable comments.


Notes

  1. Even though most of the current evolutionary terminology can be traced back to great masters in biology, it finds increasing application in the social sciences. Philosophical biologists or philosophers of biology such as Toulmin (1972), Dawkins (1976), Sober (1984), Hull (1988) and Dennett (1993) have deftly paved this way by developing a generic theoretical framework which in principle can be freed from its traditional biological subject matter. More recently, Price (1995) and Price & Shaw (1996) have adapted evolutionary theory to cover `organisational memetics'. Some readers will be struck by the apparent similarities between books written by students of technology dynamics on co-evolution (Dosi 1984, Nelson & Winter 1982) and the framework embraced in this article. Others who know work on the population ecology of organisations (Hannan & Freeman 1977, 1989) will not fail to see use of a common metaphor either. In some cases, the type of analysis performed by these theoricians may be quite similar to the view taken here. Though it would be interesting to explore the analogies between these related bodies of theory, it is beyond the scope of this article. The objective here is not to study the evolution of technology or changes in the numbers of various groups of organisations.
  2. In the DoT example, a conceptual monoculture centred around financial profitability and market forces developed. But not in all institutional structures is just one actor able to impose its conceptual frame on all the others. In structures where funds and competences are more evenly spread across the various participants, especially lower tiers of government, other concepts and arguments play a role in discussions and negotiations and are integrated into the applied conceptual systems. In federal Germany, where subnational authorities are undeniable forces in infrastructure planning, the Standardisierte Bewertung (German equivalent of COBA) is a social cost-benefit analysis covering a full range of economic, ecological, scenery, urbanistic and political motives. Lots of less ponderable criteria such as `spatial quality', `transport network effects', `intermodal connections' and `development of economically weak regions' are explicitly mentioned and valued even when they cannot be quantified.
  3. This definition of `institutions' is remarkably close to how Dosi and Nelson & Winter view `technologies'.
  4. From the two distinctions made, the first is quite common: it can be found in what legal theorists and what sociologists view as `rules' and in organisation theory it is also a crucial duo. The second distinction between conceptual and behavioural is much less spread. Simon (1982) mentions the existence of both `cognitive and institutional rules', whereas Campbell (NIG 1995b) discerns `interpretative and interactive institutions'. I can very well identify with both.
  5. Sober (1984) dedicates a full chapter of his book to the philosophical meaning of fitness. If being fit means remaining alive after the natural selection, then those who survived turned out to be fit. Such a definition denies the possibility to explain or predict fitness before the selection, leaving it no independent meaning. To be fit is to survive. However, if fitness is defined in terms of physical strength (for living beings) or semantic aptness (for words) increasing the probability of survival, it is no longer tautological. One can have a constitution well-adapted to the environment and still die, one can be a weak examplar and yet happen to survive. To be fitter is only having a bigger probability to survive.
  6. Theoretically speaking, we could even discern a fourth line of thought (related to the first) claiming that selection happens on populations of genes or populations of concepts (conceptual systems or paradigms). Some genes are more equal than others in the sense that they prestructure the operations of other genes. Equally we could say that some concepts within conceptual systems occupy more central places than others, because they determine the functioning these others have within the system. But whether natural or institutional selection occurs on genes/concepts as such or on geneplexes/conceptual systems was impossible to decide even for the gifted philosophers Toulmin (1972) and Hull (1973).
  7. Institutional evolution takes more time than conceptual evolution. Mutants have to be spread and incorporated into `brains' and then be translated to new standard and decision rules. New thinking must be transformed into new acting, which puts the power relations in existing interactive institutions at stake: innovators will always find resistance.
  8. It is also promising to relate the concepts embraced here to the work by Hannan & Freeman (1977, 1989), Morgan (1986) and Price (1995) and Price & Shaw (1996) on the evolution of organisations. This will be done in a later article.


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  © JoM-EMIT 1999


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