Peter Emmerson

1.5 An Example of Process Technology to Analyse Interdependencies.

With our present level of theoretical development in social science we will have to make do with checking out interdependencies (non-causal relationships between variables). There are some important techniques already available that can be used to examine interdependency such as the statistical method of ‘correlation’ which analyses the way two linear variables associate with one another. If we can describe compliance (levels of ‘yes-statements’) and authority (levels of social influence) as axes on a graph, we can plot any trend that occurs. My hypothesis is that high compliance will be associated with high authority and that as the levels of authority diminish so do the levels of compliance. As a result we should be able to plot a line that rises from left to right, what is called a positive correlation. The data can then be calculated to ascertain whether such a trend is significant: in other words the likelihood that the association between authority and compliance has occurred by chance – it may be that we start to entertain the idea of a real association only if the probability that it could be explained by chance is less than 0.01% (1/100).

This example is of course merely conjecture to amplify my point. However, such techniques whilst being very useful (the official advice on the danger of smoking tobacco is based on this method) do not specify a cause, they merely allow us to argue that variables co-exist with some degree of regularity: they ‘interdepend’.

Whilst correlation is very useful, it will only analyse the relationship between two linear variables. Social processes usually comprise of interdependencies involving multiples of variables as in the case I am examining here: high authority interdepends with high compliance, high pseudo-positivity, high levels of psychosocial discomfort, organisational under-performance and more. The problem is that our language is dominated by ‘system-speak’ and thus littered with conventions that are specified in terms of ‘it-statements’, geared to cause and effect explanations. This style of analysis may be OK for everyday existence where errors of prejudice may have only personal consequences. In social science however, this is not good enough as we strive to attain the highest levels of relative detachment possible, in an effort to say something more valid about the interdependencies of human life.