A LINEAR OR STAKEHOLDER MODEL OF SCIENCE?

In his book The Honest Broker (2007a), Roger Pielke sketches four different roles of the scientist. He draws an analogy to a situation in which a hungry stranger has come to a town and wants to find a place to eat.

The Pure Scientist does not to want to interfere in the stranger’s decision-making in any way. The pure scientist is only confined to the provision of basic information on a balanced diet, for example, by giving the stranger the nutrition pyramid guide published by a ministry. What the stranger does with the information is completely his own business.

The Science Arbiter offers the relevant facts only if asked specifically for them (restaurant’s level, prices). He or she acts as a resource for the decision-maker according to what the one asking for advice regards as essential. The science arbiter does not attempt to tell the stranger what to do.

The Issue Advocate wants to direct the stranger’s choice. He or she guides the stranger to eat at the restaurant favoured by the issue advocate as being the most sensible choice for one reason or another.

The Honest Broker provides the stranger with basic information about the town’s restaurants, their price level and genre, and then lets the stranger specify their selection, helping them to get the desired restaurant pinpointed. The basic characteristic of the honest broker is the attempt to expand the stranger’s knowledge of the possibilities available so that the choice can be based on the stranger’s own preferences.

All of these roles are conceivable and justifiable on their own terms. The pure scientist and the science arbiter focus on providing information, whereas the two latter types attempt to participate in the decision-making process. According to Pielke, an essential point is that a scientist cannot simultaneously act as an issue advocate and an honest broker. These roles are mutually exclusive, for the former tends to narrow the choice and the latter to expand it. The broker is Pielke’s own ideal of the scientist’s societal role.

It would seem that the pure scientist is one who offers impartial information based on impartial scientific research without trying to guide decision-making.

Everything here would seem to be right. Pielke notes, however, that the situation is not so simple and refers us to the analogy of the hungry stranger. It could well be that the particular nutrition guide published by the government ministry has been selected only after a vigorous power struggle, so that various options are merely disguised in the robes of science. Another problem is the existence of other alternative nutrition pyramids. How did this one get selected and not, for instance, a pyramid based on vegetarian eating or some other specific diet?

Thus, according to Pielke, a pure scientist may act as an issue advocate in practice, even though the nutrition pyramid does not prescribe where to eat. It is because pure scientists have the reputation of being impartial experts that their action can in fact be so-called stealth issue advocacy. Pielke describes this as “[an attempt] to swim without getting wet”.

Since the Second World War, science policy has relied on the linear model of science. This is evidenced in two ways. Firstly, it is evident in the emphasis on the importance of basic research and the requirement that research must be free from political control (Pielke 2007a:12).

Secondly, it is evident in the ideal of the unity of science. It is assumed that the precondition for a political consensus is scientific unanimity, which makes it possible to take political action. In its powerful form it means that certain scientific facts forcibly effect certain political measures.

Inherent in the linear ideal of science is the all-too-familiar idea of a certain fact or scientific body holding some compelling normative weight. It assumes, after all, the fatally-flawed premise that Hume (1711–1776) already decapitated with his guillotine: “An ‘ought’ cannot be derived from an ‘is’.” “Science can alert us to a potential problem and provide some insight about the consequences of different policy choices, but science cannot decide what choices we ultimately make” (Pielke 2010:). Kincaid (Kincaid et al. 2007:5–6) indicates that Hume was referring to a logical deduction: factual arguments never yield moral conclusions. If the premise does not include a moral judgement, the conclusion cannot have one either. The separation of values and facts is the foundation of modern western intellectual history.

In practice, climate change debates in the media and climate campaigns rely largely on the linear model when addressing the general public. According to Victor (2011:13), it may even be considered the great myth and misconception of climate policy. Hulme (2009a) gives an example of the advertising campaign of the Christian Aid organisation, which in 2007 lobbied the British government to tighten the conditions of future climate law to a reduction target of up to 90% by the year 2050.

Science was used for the justification of this demand: “Scientists have agreed that the Earth must not exceed an average temperature rise of 2°C, otherwise catastrophic

climate change will be inevitable.” Hulme comments that science is being used for normative purposes: “Implicit in this appeal to science as the basis for a lobbying campaign is that science has the authority to make definitive and universal statements about what is and what is not dangerous for people and societies and ultimately, for the world.” (Hulme 2009a:74)

Batie (2008) argues that the linear model cannot be applied to climate change because climate change deals with a “wicked” or multidimensional tangle of problems (these are discussed in more detail in Chapter 6). According to Batie, the linear model only works with “tame” problems; “wicked” problems require a different means of assessment.

Pielke does note that the linear model has received much criticism, and he brings up the so-called stakeholder model as an alternative: this is a model emphasising an open, interactive relationship between science and decision-making.

According to Pielke, when researchers ponder their relation to decision-making, two things must be recognised. The first concerns the degree of value consensus in a certain issue. Controversial issues raise political stakes to a whole new level.

Another criterion is the degree of uncertainty with regard to the issue at hand. The greater the prevailing uncertainty, the more important it is to focus on bringing up the various policy options rather than presenting simple scientific results.

Pielke notes that it would be tempting to link scientific uncertainty with political uncertainty, assuming that a decline of the former would automatically result in a decline of the latter. This assumption reflects the linear model of science. However, scientific research often increases the uncertainty of political decision-making: good science shakes black-and-white political decision-making. According to Pielke, the linear model only suits certain circumstances, i.e. those in which values are shared and uncertainty is minor. It is much more likely that the linear model leads to a system that feeds and maintains its concealed issue advocacy in science policy.

(Pielke 2007a:17–21)

Hulme also calls for a kind of stakeholder model for the introduction of local environmental knowledge¹⁰⁵ alongside universal scientific knowledge: the value of local expertise should be acknowledged. Local knowledge – often referred to as the knowledge of indigenous peoples or as traditional knowledge – has accumulated as a result of centuries of inhabitation and is often unique to a certain community or ethnic group. In respect of climate, it can contribute substantially, for instance, to solving a drought problem or observing environmental changes. (Hulme 2009a:

76–82).

Corfee-Morlot et al. (2007) consider the IPCC to largely represent the linear model. According to them, this is due to the dominance of the IPCC’s

105 In my opinion, it could be called “local environmental wisdom.”

techno-rational and analytical tradition in decision-making relating to the environment. They demand that there should be a broader understanding of social processes and political problems, which would better respond to the global problems of environmental change. Between the positivist-realistic ideal of science and the interpretive-constructivist model that emphasises the social dimension, they suggest a co-construction hybrid model. It would combine the strengths of both: social understanding with a scientific research approach.

(Corfee-Morlot et al. 2007:2743–2744)