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fluence evaluation of flood control proposals. The effect of these factors is to bias a group for or againsl flood conlrol proposals and establish a general under- lying lendency to approve or reject them. If the atti- tude were negative a proposal would have to overcome this generalized conditioned response, or attitude, or be rejected. If for example, people with urban back- grounds, or home ownership, or some other character. istic were likely 10 approve a flood control proposal withoul specific knowledge about ii, this lendency or predisposition would be an example of a biasing fac- tor. Such a factor may have a separate effect and also be usefui in an Acceptance Funclion. For instance, two variables used in Ihis study were experience with flooding and proximity of flood experience 10 presenl residence. Either of these may cause a tendency for favoring control measures and may alter the respon- denis' perception of the effectiveness of a particular flood control method. The relative importance of eilher of Ihese two variables may also depend on the evaluation judge's knowledge of the proposal. For example, a person who lends to be in favor of flood control because he perceived a need may reject a parlicular proposal when he learns that it is less efficient than another method. A "labeling" phenonemon, or conditioned response to a symbol, may occur because of the name "flood control." This type of response may be re- moved with sufficient knowledge. 6 The evaluation of a flood control proposal is determined by adding the effect of predisposing char- acteristics and the Acceptance Functions discussed in Ihe preceding section 7 as shown in Figure 4.4. This diagram illustrates the conceptualization behind the equation applied to every agency and the public in the model. For example, suppose a project would actually cost $3,000,000 and add a tax of $150 per taxpayer in the affecled area. The perceived cost by members of the population, however, would not necessarily be this dollar cost; in fact, Ihe perceived cost may nol be in dollars9 The perceived cost would be "high" to "low" depending on a person's circumstances and back- ground. What is considered "low" by one group may be considered "high" by anolher. The perceived char- 6The idea of "labeling" and its dynamics is interesting in itself. A label may have meaning so long as the person judging does not have reason to doubt the validity of the label. 7The weightings of each term, factor, or Acceptance Function is done by Uge of regression analysis. 8The perceived cost could accurately be expressed in dollars only if the dollar figures used were proportionate to the meanings which the costs have to all respondents. It would be easier to use a scale directly measuring this "perceived cost:" in non-monetary units. acteristics were measured by scales of "low" to "high" in calibrating the main equation developed in this re- port. The Distortion Factors in Figure 4.4 reflect the differences between the designed characteristics of a proposal and the perceived characterislics. The agen- cy perceptions are assumed 10 be the same as Ihose of the designer because of information exchange dur- ing the design of a proposal. Distortion Factors should perhaps be used to account for I)-an agency's perception of other agency's proposals, and 2) Ihe public's evaluation of a flood control proposal, but this is not done in the present model. Since the pub- lic's perceplion of flood control proposal characteris- tics was directly measured, any distortion is already included. The assumption that the agency opinion is correctly perceived is justified on Ihe basis of the pub- licily given to flood.control decisions by an agency. The variables shown in Figure 4.4 are not ex- haustive. Other consigerations such as safety and generality of benefit may be included (see Andrews, and Geertsen, 1974a: 33-35). Also effecls on num- erous "other groups" may be usefully represented in the model. Acceptance Functions for other groups affecled can be as many as there are groups whose opinions are significant. The model can be expanded by repeated applicalion of the basic equation based on this conceptualization of the decision process with groups being connected to each other through Accepl- ance Functions of this last type. The model can be made as complicated as desired by adding more inter- actions as they are observed. Special Interest Group Functions In applying the equalions based on the concep- tualization of the decision process shown in Figure 4.4, a problem develops in that the results predict the average attitude of the public, and people in unusual situations have a disproportionate influence on the outcome of the total process. Special interest groups act 10 block or promote changes. They are vocal and may be influential. Expa1l8ion Effect A concern or value is latent and unimportant until it is threatened, when its imporlance is suddenly expanded. When this vaiue becomes a group concern, whether by an existing group or one newly organized, its public role is expanded greatly. The resulting "ex- pansion effect 11 is psychological, cognitive, and emo- tional and often becomes a "cause" for a specialinter- est group. This latent-expansion phenomena needs to be identified and represented in a social system for decision-making. In an ecological special interest group, for example, potential effects on an ecological S3