Several methods have been developed that incorporate some means of scaling effects and weighting the importance of various elements, thus resulting in a mathematical means of combining magnitude and significance for an overall evaluation of project impact. Technically these methods fall under the rubric of checklists, but they go far beyond what checklists provide.

Scaling of effects addresses issues of magnitude and is based on a numerical system in which the highest number represents a very good effect and the lowest number represents a very adverse effect. The mid-point would be an average effect, or a neutral one. This can be used alone to determine some composite score for magnitude or it can be combined with a weighting scheme to incorporate considerations of importance or significance.

With weighting, values are given to elements of the environment (or of a proposal) based on their relative importance or significance. The end result can be either a total score or a group of scores representing various "sectors" of the environment.

This category of methods is particularly useful because it combines measures of magnitude and significance in a highly organised format. As a result, this is a very systematic approach that is valuable for analysing alternatives. The approach incorporates a large amount of data that may not otherwise be readily comparable. Thus, the method provides a means of synthesising a great deal of information while still retaining measures of magnitude and significance.

Judgement is inherent in this approach, particularly when importance values, or weights, are assigned to individual components or elements. "Importance" or "significance" can mean many different things, so it is necessary to define it very carefully. In addition, when scaling effects, it is necessary to be explicit about what the values mean. The method works best when the scales relate to real, measurable changes, as in water quality or employment levels. Given appropriately detailed documentation, the scaling and weighting values decided upon by different people should not vary much.

There has been some discussion among both researchers and practitioners about the validity of adding or multiplying numbers that do not represent actual intervals, but instead relate to an ordinal scale (i.e. where numbers represent rankings or categories in a hierarchy, rather than a measurable interval). In addition, an aggregate final score tends to mask individual components that represent particular strengths or weaknesses in an activity. This has been countered with the argument that a total score is most useful for decision-makers and that it is valid as long as the method itself is internally consistent.

In any case, the method is not valid if the basis for assigning scales and weights is not clearly defined in an accompanying document. Further, some attempt has been made to overcome these problems by providing semi-aggregate scores, sometimes by sector or category (i.e. ecologic, physical/chemical, and social categories), and allowing analysis to follow from that with full recognition of the trade-offs that may be involved.

SCORES TOTAL 118

5 = Crucial 3 = Important 1 = Minor Importance

4 = Outstanding 2 = Average 0 = Deficient