Next: 3 OVERVIEW OF LIGHT AND CRIME STUDIES Up: OUTDOOR LIGHTING AND CRIME, PART 1: LITTLE Previous: 1 INTRODUCTION Contents
Early explanations of natural phenomena and human behaviour were derived by the method of intuition (eg ancient concept of Earth as the centre of the universe) or the method of authority (eg bishop announced date of creation as 4004 BC). These methods (eg Martinez-Papponi 2000 [66]) of trying to increase knowledge have been superseded by scientific method in the last four centuries, which is not to say that intuition and standing have no place in scientific progress.
Intuition and authoritative guidance assist expedience in the decision making of everyday life. However, they tend to intrude from there into public debate on contentious issues that require scientific input as a necessary part of resolution. Environmental issues provide many examples. The ends may encourage misuse of authority but seldom if ever justify it.
The effectiveness of rigorously applied scientific method is firmly established. But if some applicable rules and procedures are not followed properly in a particular study, the conclusions may be flawed. Described below are some of the more common traps that await the unwary and sometimes even the cognoscenti. This also indicates some of the reasons why, even in favourable circumstances, it is not at all simple to make a reliable determination of the extent to which outdoor lighting does or does not affect crime.
Human behaviour is often studied in laboratory settings with extraneous factors eliminated or held constant by design and conduct of the experiment so that the cause-effect hypothesis being investigated is given the best prospect of a fair test and a reliable result. This `reductionist' approach can be and often is applied outside the laboratory but as the complexity of the circumstances increases it also becomes more difficult to design experiments with full counterbalancing for all extraneous factors that could conceivably influence or confound the results. Results from such quasi-experiments tend to be less reliable, possibly to the point of being useless or even misleading in some cases.
Real-world aspects of the lighting and crime issue often appear to be too complex or are otherwise unsuitable for investigation with laboratory experiments. Systems outside laboratory settings tend to be on such a large scale that deliberate manipulation of variables for experimental purposes may be impracticable, and opportunistic use of regional changes (eg relighting for economic reasons) may be accompanied by undesirable constraints on the use or extent of experimental controls.2 For behavioural studies in general, ethical aspects require no tangible risk of harm to individuals. Fully informed prior consent of individuals to be experimental subjects is required for laboratory experiments but may be impracticable for quasi-experiments.
Thus it would seem that deliberate on-off manipulation of outdoor lighting in populated areas might be unacceptable as a means of seeing what happens to the crime rate, regardless of any benefit that a decisive result might bring. It would certainly be wrong to reduce outdoor lighting so far as to reproduce the blackout conditions3 of World War 2, for example, as there were high risks of traffic accidents, falls, and drownings in ponds and watercourses when people had to make their way about in natural darkness at night (HSHF 2002 [47]). But vision science indicates that present outdoor lighting could often be reduced by one or more powers of ten (`log units' in vision science jargon) without introducing undue mobility hazards.
Other ways of studying large complex systems have been developed within the constraints of scientific method. Top-down analysis of human activity systems (eg Checkland 1981 [20]) can sometimes give unique insights, but no specific example of its use has been found in connection with the lighting and crime issue. Another method is simply the purposeful painstaking observation and analysis of a system that is generally unavailable to deliberate manipulation, as in astronomical observation of the universe. Associations between observable characteristics may be sought on the basis of results of laboratory experiments. Useful statistical and logical inferences may be possible, allowing an ongoing cycle of extending and refining knowledge.
Scientific method allows development of hypotheses and their observational or experimental testing and analysis in a systematic cycle. This is the most effective way in which new knowledge can be gained. Where observations of a whole population are impracticable, results from samples may be generalised to the whole population. Usually, however, all else being equal, the smaller the sample then the greater is the risk of error in generalising.
Scientific method requires minimisation or preferably the effective elimination of effects of both deliberate and unwitting bias by researchers. Ideally, researchers should be disinterested in which way their results will turn out. Human nature being what it is, this condition might seldom be achieved absolutely. For example, inconclusive or null findings are known to have less value than useful findings in academic career advancement, and lack of self-interest in such things appears to be rare. However, ``Academic self interest is a legitimate part of the motivation to conduct research'' (Levinsky 2002 [57]).
Regardless of the intellectual probity of individual researchers, compliance with the zero bias condition is equivocal when the results may have appreciable outcomes, beneficial or adverse, on an organisation that controls, funds or otherwise supports the research or pays for publication of the results. Unfortunately, such situations appear to influence authors far more than might be expected. There are known cases in which scientific papers and reports have been markedly compromised by this kind of bias. Numerous examples have been detected in research on efficacy of pharmaceutical drugs (Angell 2000 [2], Bodenheimer 2000 [12], Drazen and Curfman 2002 [30], van Kolfschooten 2002 [113]), on tobacco smoking and `health' (ie disease), on asbestos and cancer, and on the traffic hazards of vehicle tinted glazing, sponsored in each case by one or more industry stakeholders (Clark 1995 [21]). This seems bad enough, but compared with the problems of financial conflicts of interest, ``nonfinancial conflicts of interests are more subtle yet more pervasive and cannot be eliminated'' (Levinsky 2002 [57]). Conflict of interest is of concern in science generally, not just in the medical and pharmaceutical areas (Laurin 2002 [56]).
Of related concern is the use of industry-paid technical experts to prepare, present and examine adversarial evidence about the effects of light at night in municipal planning applications and appeals. It would appear to be more in the public interest if those judging the issue were able to receive independent non-adversarial advice, even if this were from experts nominated by interested parties. In the present context, planning and environment organisations and authorities, law enforcement agencies and the lighting and power industries all need to avoid bias because of its undesirable capacity to move a judgement away from the result merited by the facts. Ultimately the whole community is likely to lose out from unjustifiably influenced decisions, regardless of which party gains short-term benefits from the judgement.