Formalised rules

Occasionally there is tacit recognition of the informal structure by the formal since the informal level allows for practical interpretation of rules and procedures that can place restrictions on achieving enterprise targets. This flexible interpretation of the formal rules may be to the common organisational good, but may also be detrimental where they concern safe working practices. The fact of these informal interpretations can be seen in the dramatic effect of a work-to-rule in a formalised rule-based organisation. 

Formalised rules. Some accidents start raising concern and have the potential to affect corporate liability. Organisations thus draft mles, based on past experience, to help users in some specific activity. Examples can be found in company procedures and mles of classification societies. 

The need for rapidly accessible estimation of toxicity has led to the development of software and other algorithms that will generate estimations of toxicity, usually for organic compounds [79] such methodology is termed an expert system, which has been defined [34] as any formalised system, not necessarily computer-based, which enables a user to obtain rational predictions about the toxicity of chemicals. Essentially, expert systems fall into two classes— those relying on statistical approaches and those based on explicit rules derived from human knowledge. 

Of conrse, many reflections are possible from a regnlar lattice, and if the set of vectors snch as h is represented then we can graphically visualise all the reflecting planes and consequent reflected directions in the crystal. We have dednced virtually all the rules already, but we formalise the description below. 

In terms of regulatory risk management, the SOMS does not detail rules for EU action corresponding to each hazard and use categorisation. Similarly, while the RCEP presents a wide and detailed set of recommendations to make increased use of a wide range of risk management and policy instruments, it does not present these as a formalised structure for EU decision-making. 

Problems in chemistry sometimes require the differentiation of functions which are more complicated than those discussed so far. In the previous chapter it was seen how to differentiate a function multiplied by a constant, and sums and differences of simple functions. For completeness, these rules are formalised here, before products and quotients of functions are considered. 

These ideas can be formalised in terms of statistical mechanics to some extent, and an outline of the main ideas is given in the following section. We remark parenthetically that there are profound difficulties confronting the definition of an aggregate. The nature of the hydrophobic free energy of transfer of a hydrocarbon from water to the hydrophobic core of a micelle can be measured, but its temperature dependence is not understood because it depends on water, an unknown quantity. For the same reasons, solution theory, does not even tell us whether mole fractions or mole volumes are the correct ratios to use to determine entropy. However, provided certain assumptions are allowed [62-65], then simple rules emerge. The rules are if v is the hydrocarbon chain volume, a the head-group area, and 1 of an optimal... 

We adopted the first approach anotlier company adopted the second. In both cases, it is important to note tliat the specifications (our output and their input) are written in fonnal languages automatic translation between the two notations is therefore possible. If we detennine user requirements and formalise a specification in our notation, and they accept a (formal) specification in their notation, then we can collaboratively proceed from user requirements to executable code by rule and with very little manual involvement (and therefore very few errors), provided only tliat a translator exists between tlie two fonnal languages. 

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