A recent disciplinary offshoot of criminology, crime science (CS) defines itself as “the application of science to the control of crime.” One of its stated ambitions is to act as a cross-disciplinary linchpin in the domain of crime reduction. Despite many practical successes, notably in the area of situational crime prevention (SCP), CS has yet to achieve a commensurate level of academic visibility. The case is made that the growth of CS is stifled by its reliance on a model of decision-making, the Rational Choice Perspective (RCP), which is inimical to the integration of knowledge and insights from the behavioral, cognitive and neurosciences (CBNs).
“Normally, conservatives extol the magic of markets and the adaptability of the private sector, which is supposedly able to transcend with ease any constraints posed by, say, limited supplies of natural resources. But as soon as anyone proposes adding a few limits to reflect environmental issues — such as a cap on carbon emissions — those all-capable corporations supposedly lose any ability to cope with change.” Krugman – NYT
From Clive Hamilton via Technology Review,
If humans were sufficiently omniscient and omnipotent, would we, like God, use climate engineering methods benevolently? Earth system science cannot answer this question, but it hardly needs to, for we know the answer already. Given that humans are proposing to engineer the climate because of a cascade of institutional failings and self-interested behaviours, any suggestions that deployment of a solar shield would be done in a way that fulfilled the strongest principles of justice and compassion would lack credibility, to say the least.
This time of year, systems thinkers should eschew sugar plum fairies and instead dream of Industrial Dynamics, Appendix N:
Self-generated Seasonal Cycles
Industrial policies adopted in recognition of seasonal sales patterns may often accentuate the very seasonality from which they arise. A seasonal forecast can lead to action that may cause fulfillment of the forecast. In closed-loop systems this is a likely possibility. The analysis of sales data in search of seasonality is fraught with many dangers. As discussed in Appendix F, random-noise disturbances contain a broad band of component frequencies. This means that any effort toward statistical isolation of a seasonal sales component will find some seasonality in the random disturbances. Should the seasonality so located lead to decisions that create actual seasonality, the process can become self-regenerative.
Self-induced seasonality appears to occur many places in American industry. Sometimes it is obvious and clearly recognized, and perhaps little can be done about it. An example of the obvious is the strong seasonality in items such as cameras sold in the Christmas trade. By bringing out new models and by advertising and other sales promotion in anticipation of Christmas purchases, the industry tends to concentrate its sales at this particular time of year.
Other kinds of seasonality are much less clear. Almost always when seasonality is expected, explanations can be found to justify whatever one believes to be true. A tradition can be established that a particular item sells better at a certain time of year. As this “fact” becomes more and more widely believed, it may tend to concentrate sales effort at the time when the customers are believed to wish to buy. This in turn still further heightens the sales at that particular time.
A little poem for congress, and people embroiled in conflict everywhere:
The Noble Art
The noble art of Losing Face
may one day save the Human Race
and turn into eternal merit
what weaker minds would call disgrace.