I was watching an interesting show on Link TV ( A very Loony Lefty “Public” TV channel on the satellite dish – which I watch from time to time as they have some irritant value for stimulating pearls of ideas…). It was about The Commons. The general thesis was that The Commons has been steadily usurped by the Evil Market to the detriment of us all. ( I may do a bit on that in some other posting…) There was also a pointer to Elinor Ostrom who got a Nobel prize for Economics for her work on the commons (that, predictably, claims to show there is no real “Tragedy of the Commons” and we can all be happy to make our communes and live our communal lives free of evil exploitation…) Yes, I’ve got a lot to say about that, but it will have to wait. (The ‘short form’ is that there IS a “Tragedy of the Commons” but it can be overcome in some circumstances via a kind of governance. To define that governance as non-government and then conclude there is no “Tragedy of the Commons” is, er, quite a stretch. But yes, we can and do form self governing “commons” that work.)
This was in the context of a comment by BlueIce2HotSeas on another thread that had me thinking about how we got here, why the participants protect their turf, and how to get out of this Tragedy of Tyrannies. https://chiefio.wordpress.com/2010/11/18/what-trend/#comment-8966
So I’d now postulate that Climate Science is subject to what I will christen “The Tragedy of Small Tyrannies”. (And perhaps all science suffers in this way).
The Tyranny of Small Decisions
Along the way, I was reminded of the Economic Problem described as the Tyranny Of Small Decisions. I’ll provide a pointer to the wiki for that topic for folks wanting an introduction. (And since, in a stellar example of the failure of the commons, the Wiki tends to get re-written when a conservative point of view references it, I’ll quote the whole article below as documentation of what it WAS prior to The Tragedy, should that happen yet again… It’s only happened about 60% of the time in the bits I’ve audited. Then again, that isn’t a strongly AGW related article.)
The basic idea is that a series of small decisions, each one rational, can lead to poor or even very bad outcomes. I’ve seen this happen quite often, and it’s a fairly well attested effect.
So what does this have to do with Global Warming?
I suspect that it explains how we ended up with the current global panic over nothing.
The process of “Climate Science” (and perhaps all science as presently practiced) is subject to The Tyranny Of Small Decisions. That is the thesis of this posting.
In particular, I think there are three clear examples. Ideas that are now excepted as central to creating our “Global Average Temperature” but are in fact Small Tyrannies that have lead researchers astray.
1) “Climate” defined as a “30 Year Average of Weather”
2) The Reference Station Method
3) Grid / Box Anomalies
All three are part of the “Peer Reviewed Literature”, so become authoritarian and thus subject to tyrannical use. Each has a significant flaw or limitation that is ignored in their application (and thus lead to the erroneous conclusion that the world is warming, when it’s really cycling in hundreds of years or less time scales in a general very long term (thousands of years) downtrend, or cooling trend). So we confound cyclical behaviours with trend.
We will look at each one in turn, and how I think they act as a Tyranny of Small Decisions.
In “Climate Science”, they define climate in terms of a 30 year period. Yet we know this is not truth. It is a choice of ‘convenience’. In prior times (and other fields) climate was defined in terms of precipitation, terrain, latitude, altitude. That is how Geology has treated climate. Things that do not change very fast, and that produce highly persistent patterns of what lives in a place and what the geography looks like.
The Sahara has been a “Desert Climate” for thousands of years. The Mediterranean has been a “Mediterranean Climate” for similar thousands of years. During the Little Ice Age as well as during the Roman Optimum. These things do not change on decade time scales. But weather does. We know of 60 year cycles of weather, for example. The Pacific Decadal Oscillation. And these show a ‘warming” from 1950 to 1998, but one that is simply not important to climate. It IS important to weather, but will once again turn down to a cooling trend of ’30 year average weather’ as the PDO turns.
(Notice the recent cold turn…)
By accepting the small lie that “30 year average of weather” is “climate” we accept one of the first Small Tyrannies and head down the path to the Tyranny Of Small Decisions. If “30 year average weather” is just weather, not climate, then all of “Climate Science” as practiced today falls apart. Weather is known to be chaotic and subject to non-linear divergences with time and is not subject to accurate long term modeling. Weather is known to have long term cyclical patterns that are beyond the available data (in terms of sample time and area, we violate Nyqist Sampling requirements).
Basically, if you define climate as needing a 1000 year time base to see it without cycles interfering, then you admit that we have not got the instrumental data record to know anything about it. (And we know of at least one 1470 year cycle. Bond Events.)
The Reference Station Method
This says that you can compare two stations at one point in time and find how they relate to each other, then use that to recreate missing data in other time periods. This is from a peer reviewed paper, so is accepted as simply true. But the paper applies to a limited scope of time and space. It does NOT cover the entire length of time of known weather cycles. So, for example, the tendency for stations more inland or more at altitude to change their relationship to those at a sea coast as the PDO cycle changes is not recognized nor ‘corrected’. And the tendency for, say, a grass field in 1950 to have a different relationship today (now that it’s a square mile of tarmac at an International Airport) is also ignored.
The “peer reviewed” Reference Station Method is accepted as valid for all times, all places, and all conditions. While the paper itself was for a short time in a small space and specific conditions. This “small decision” has an error term, but the error term is assumed to not exist. RSM is applied to any stations at any time up to 1200 km away from each other with no allowance for the impact of PDO cycles (or other cycles) nor land use changes nor equipment changes nor process changes nor even any proof that you can apply it recursively (first to individual stations, then to UHI ‘corrections’ and ‘homogenizing’ and then to ‘grid / boxes’) without accumulating excessive errors.
Grid / Box Anomalies
There is a frequently heard refrain that by using ‘anomalies’ we can average temperatures. Clearly if you have a place that’s 10 degrees and another that is 20 degrees, putting more thermometers in one of them than you put in the other will change the average. But if you only look at the “change of temperature over time” of the thermometers, you could average that together without caring about ‘how many’.
That change over time is called ‘the anomaly’ of the thermometer.
So put 2 in the 10 degree place and one in the 20 degree place, you would get an average of 10+10+20 = 40 then divide by 3 is 13.33 degrees. Move one to the 20 degree place and you get 10+20+20 = 50 then divide by 3 is 16.66 degrees. That 3.33 degree difference is entirely an artifact of changing the location of the thermometers, not a real change of temperatures.
(I’ve taken flack from folks complaining that I’ve averaged temperatures instead of doing anomalies when they have not understood that I was doing it to ‘characterize the data’. That is, to see how much the averages are impacted by such things as instrument change. For small places, like an island or two, you can directly average temperatures for well stabilized instruments, and I’ve done that too. It’s a convenient way to see the impact of adding or removing one particular instrument. Just don’t think it says anything about climate… It’s to tell you the size of the data problem. The “error” is to think that non ‘self to self’ anomaly processing fixes instrument change issues and splice issues.)
The idea is that if you just look at the change of each thermometer over time, you can ignore the change of location issue. So if we assume that each thermometer warmed by 1 degree, our two calculations would be:
10 to 11 is +1 while 20 to 21 is +1. 1+1+1 / 3 = 1
for the other case, with 2 thermometers in the 20 degree place, we still have:
1+1+1 / 3 = 1
Hey! It works!
(No real surprise there… I’ve taken a lot of flack from folks who seem to think I don’t know this. What they “don’t get” is that my concern comes out of the next issue, not this trivial case…)
But is that what “climate science” does?
That example is what I call a ‘self to self’ anomaly. Each thermometer is compared only to itself.
The problem comes in when you don’t have a thermometer compared to itself, but rather compared to some other thermometer. That isn’t really an ‘anomaly’ in the pure sense. It has more in common with our ‘move the thermometer’ problem. It’s a kind of splice of different things.
The “fix” is supposed to be The Reference Station Method. The idea is that a station can be ‘adjusted’ by comparing it’s past history to another station, then filling in the missing data. So we would say that we can compare our 10 degree station with our 20 degree station and say “gee, they both move by 1 F at the same time”. All well and good. And accepted as peer reviewed. But this is where it goes off the rails.
It’s accepted and peer reviewed based on a small sample in time and space, and done only one time in a row. One station to another in one small span of time.
What if the relationship is 1:1 in the negative phase of the PDO and 1:2 in the positive phase? Then that “30 year average” used as the baseline in codes like GIStemp starts to be a major error source.
Then in the temperature codes, like GIStemp, The Reference Station Method (RSM) is applied several times in a row. Has THAT ever been peer reviewed? It is applied to stations all over the planet. Was THAT ever peer reviewed? (Or only the small sample of data that was in the original paper?) It is applied over a century of data, with different thermometers in different places and using different technology in the collection and ‘adjustment’ of the data. Not exactly what was done in the original work. So we take this RSM and think that somehow it will be just fine for filling in data in any time and place (with no regard for PDO and similar cycles and with no regard that the ‘volatility’ of a station might change over time – so things like adding asphalt vs a grass field at an airport is assumed to have no impact on the ‘reference’).
OK, that’s part of the issue. That creates the error term. But then we think that by making a ‘basket’ of these data in one period of time and comparing it to a different basket of data from different thermometers in a different period of time to create an ‘anomaly’ for that location will fix it; the fact that we are averaging these thermometers (and non-thermometer RSM fabricated data items) in a particular place on the planet is somehow not comparing different things. That it’s just like a ‘self to self’ anomaly.
But it isn’t.
The reality is that we are really making a ‘data splice’ but hiding it via the Reference Station Method and ‘grid / box anomalies’. We think that somehow by making an average of 2 Volkswagons in 1950 and 2 Mercedes today then comparing the two baskets, it’s a valid result. That cars are going up in size over time. But even if we compared a 1950 VW to a 1950 Mercedes and applied THAT correction factor to our 2010 Mercedes, we would still have an error term. The two have not changed at exactly the same pace. And making a “car / box anomaly” out of the two sets of data will NOT remove that error term.
But “climate science” has accepted the notion that a “grid / box anomaly” is just as good as a ‘self to self’ anomaly, when it isn’t. And it has accepted that the RSM can be applied in all times and spaces and recursively, even when not proven.
So by accepting THAT ‘small decision’ we accept invalid data splicing as valid.
Think A Minute
But even modest time spent thinking about it and you realize that a Liquid In Glass thermometer in a Stevenson Screen on the grass field of your local airport in 1920 will NOT be recording the same thing as an ASOS station surrounded by a square mile of tarmac today. And averaging 3 of them in a “grid box” in the past and comparing them to 2 different ones in that “grid box” today is just not going to remove that error term. Further, if those first 3 were near the lake, and the 2 today are away from the lake at the airport, the change in ‘volatility’ (called ‘moderation’ when it comes to water effects) will also not be removed by averaging them together into a ‘grid box’.
That some paper was accepted for publication in one narrow context lets the idea be used in all cases even those well beyond the scope of the paper. A ‘small decision’ that then justified accepting splices of very different thermometers in very different places over very long times. We are then supposed to accept this uncritically.
The simple fact is that the only real ‘anomaly’ is comparing a thermometer to itself. An ‘anomaly’ made by comparing one box of thermometer in one set of micro-locations in one period of time to a different box of different thermometers in a different set of micro-locations in a different period of time is properly called “a splice”. And no matter how carefully done, it’s still just a splice and subject to all the failures of spliced data.
But “climate science” accepts this ‘small decision’ and thus accepts the “Tyranny Of Small Decisions” that it then generates. Belief in a False Precision and belief that a splice is error-free.
But Wait, There’s More!
All throughout the debate there is talk of the Global Average Temperature. But at it’s core, that very concept is broken. An average of temperatures is a bogus concept.
This has to do with the difference between intensive and extensive properties. Heat can be averaged, but temperature can not. (Heat is the product of temperature AND mass AND specific heat. If you are missing one of those, you don’t have all the information you need to reach a conclusion. Mix two pots of water, one at 10 degrees and the other at 40 degrees. What is the resulting temperature? You can’t know unless you get the mass of water in each pot. Was that 10 F or C? If it was in F, then you have the problem of the Heat of Fusion of the ice as you melt it…)
Yet we are expected to accept uncritically the “small decision” to use temperature increase as a proxy for heat gain; when it isn’t.
Mix that with the broken way we do ‘grid / box anomalies’ and use RSM out of all reasonable context and suddenly it makes sense why codes like GIStemp find consistent temperature rises (with the presumption of heat gain) yet long lived stations tend to show no net temperature rise, no trend of heat gain.
So my basic thesis in this posting is simple:
Each of those decisions can be defended to the point where the case can be made that it’s a “small decision” to accept that tiny bit of error and tiny bit of imprecision. To accept that it isn’t quite right, but not completely wrong, so just forget about it. But that then leads to conclusions that are completely wrong and totally out of touch with reality at a policy level.
This sort of “Post Modern Science” is fatally prone to The Tyranny of Small Decisions (especially when they are hidden deep in inscrutable computer codes and programs, and defended with the arcane rules of Peer Review – especially with suborned peers and ‘pal review’ as Climategate illustrated.) and the policy results of following such a chain of Small Decisions would be one very Large Disaster.
And thus we end up at The Tragedy of Small Tyrannies and the need to throw off tyrants, even the small and petty ones…
Preserving The Wiki
As much as I like the NOTION of a commons encyclopedia and use the content when possible, it’s just not a stable platform to use in links as a reference. Politically driven zealots re-write it when a reference does not suit their agenda so I’ve learned that I need to preserve it as it was if I point to an article. Sigh… To that end, here’s the wiki text as of now:
Tyranny of small decisions
From Wikipedia, the free encyclopedia
The tyranny of small decisions refers to a phenomenon explored in an essay by that name, published in 1966 by the American economist Alfred E. Kahn. The article describes a situation where a number of decisions, individually small in size and time perspective, cumulatively result in an outcome which is not optimal or desired. It is a situation where a series of small, individually rational decisions can negatively change the context of subsequent choices, even to the point where desired alternatives are irreversibly destroyed. Kahn described the problem as a common issue in market economics which can lead to market failure. The concept has since been extended to areas other than economic ones, such as environmental degradation, political elections and health outcomes.
A classic example of the tyranny of small decisions is the tragedy of the commons, described by Garrett Hardin in 1968 as a situation where a number of herders graze cows on a commons. The herders each act independently in what they perceive to be their own rational self-interest, ultimately depleting their shared limited resource, even though it is clear that it is not in any herder’s long-term interest for this to happen.
* 1 The Ithaca railroad
* 2 History of the idea
* 3 Environmental degradation
* 4 Counters
* 5 See also
* 6 Notes
* 7 References
The Ithaca railroad
Abutment of the Ithaca-Auburn Short Line bridge
The event that first suggested the tyranny of small decisions to Kahn was the withdrawal of passenger railway services in Ithaca, New York. The railway was the only reliable way to get in and out of Ithaca. It provided services regardless of conditions, in fair weather and foul, during peak seasons and off-peak seasons. The local airline and bus company skimmed the traffic when conditions were favourable, leaving the trains to fill in when conditions were difficult. The railway service was eventually withdrawn, because the collective individual decisions made by travellers did not provide the railway with the revenue it needed to cover its incremental costs. According to Kahn, this suggests a hypothetical economic test of whether the service should have been withdrawn.
Suppose each person in the cities served were to ask himself how much he would have been willing to pledge regularly over some time period, say annually, by purchase of prepaid tickets, to keep rail passenger service available to his community. As long as the amount that he would have declared (to himself) would have exceeded what he actually paid on the period–and my own introspective experiment shows that it would–then to that extent the disappearance of the passenger service was an incident of market failure.
The failure to reflect the full value to passengers of keeping the railroad service available had its origins in the discrepancy between the time perception within which the travellers were operating, and the time perception within which the railroad was operating. The travellers were making many short term decisions, deciding each particular trip whether to go by the railroad, or whether to go instead by car, bus or the local airline. Based on the cumulative effects of these small decisions, the railroad was making one major long run decision, “virtually all-or-nothing and once-and-for-all”; whether to retain or abandon its passenger service. Taken one at a time, each small travel decision made individually by the travellers had a negligible impact on the survivability of the railroad. It would not have been rational for a traveller to consider the survival of the railroad imperilled by any one of his particular decisions.
The fact remains that each selection of x over y constitutes also a vote for eliminating the possibility thereafter of choosing y. If enough people vote for x, each time necessarily on the assumption that y will continue to be available, y may in fact disappear. And its disappearance may constitute a genuine deprivation, which customers might willingly have paid something to avoid. The only choice the market offered travellers to influence the longer-run decision of the railroad was thus shorter in its time perspective, and the sum total of our individual purchases of railroad tickets necessary added up to a smaller amount, than our actual combined interest in the continued availability of rail service. We were victims of the “tyranny of small decisions”.
History of the idea
Thucydides (ca. 460 B.C.-ca. 395 B.C.) stated:
[T]hey devote a very small fraction of time to the consideration of any public object, most of it to the prosecution of their own objects. Meanwhile each fancies that no harm will come to his neglect, that it is the business of somebody else to look after this or that for him; and so, by the same notion being entertained by all separately, the common cause imperceptibly decays.
Aristotle (384 B.C.-322 B.C.) similarly argued against common goods of the polis of Athens:
For that which is common to the greatest number has the least care bestowed upon it. Every one thinks chiefly of his own, hardly at all of the common interest; and only when he is himself concerned as an individual. For besides other considerations, everybody is more inclined to neglect the duty which he expects another to fulfill; as in families many attendants are often less useful than a few.
Thomas Mun (1571–1641), an English mercantilist, commented about decisions made with a myopic, small time perspective:
[T]hey search no further than the beginning of the work, which mis-informs their judgements, and leads them into error: For if we only behold the actions of the husbandman in the seed-time when he casteth away much good corn into the ground, we will rather account him a mad-man than a husbandman: but when we consider his labours in the harvest which is the end of his endeavours, we find the worth and plentiful increase of his actions.
Eugen von Böhm-Bawerk (1851–1914), an Austrian economist, observed that decisions made with small time perspectives can have a seductive quality:
It occurs frequently, I believe, that a person is faced with a choice between a present and a future satisfaction or dissatisfaction and that he decides in favor of lesser present pleasure even though he knows perfectly well, and is even explicitly aware at the moment he makes his choice, that the future disadvantage is the greater and that therefore his well-being, on the whole, suffers by reason of his choice. The “playboy” squanders his whole month’s allowance in the first few days on frivolous dissipation. How clearly he anticipates his later embarrassment and deprivation! And yet he is unable to resist the temptations of the moment.
As a result of many small decisions, and without the issue being directly addressed, nearly half the marshlands were destroyed along the coasts of Connecticut and Massachusetts
In 1982, the estuarine ecologist, William Odum, published a paper where he extended the notion of the tyranny of small decisions to environmental issues. According to Odum, “much of the current confusion and distress surrounding environmental issues can be traced to decisions that were never consciously made, but simply resulted from a series of small decisions.”
Odum cites, as an example, the marshlands along the coasts of Connecticut and Massachusetts. Between 1950 and 1970, almost 50 percent of these marshlands were destroyed. This was not purposely planned, and the public may well have supported preservation had they been asked. Instead, hundreds of small tracts of marshland were converted to other purposes through hundreds of small decisions, resulting in a major outcome without the overall issue ever being directly addressed.
Another example is the Florida Everglades. These have been threatened, not by a single unfavorable decision, but by many independent pin prick decisions, such as decisions to add this well, that drainage canal, one more retirement village, another roadway… No explicit decision was made to restrict the flow of surface water into the glades, or to encourage hot, destructive fires and intensify droughts, yet this has been the outcome.
With few exceptions, threatened and endangered species owe their predicament to series of small decisions. Polar bears, humpback whales and bald eagles have suffered from the cumulative effects of single decisions to overexploit or convert habitats. The removal, one by one, of green turtle nesting beaches for other uses parallels the decline in green turtle populations.
Cultural lake eutrophication is rarely the result of an intentional decision. Instead, lakes eutrophy gradually as a cumulative effect of small decisions; the addition of this domestic sewage outfall and then that industrial outfall, with a runoff that increases steadily as this housing development is added, then that highway and some more agricultural fields. The insidious effects of small decisions marches on; productive land turns to desert, groundwater resources are overexploited to the point where they can’t recover, persistent pesticides are used and tropical forests are cleared without factoring in the cumulative consequences.
Considering all of the pressures and short-term rewards that guide society toward simple solutions, it seems safe to assume that the “tyranny of small decisions” will be an integral part of environmental policy for a long time to come. – William Odum
An obvious counter to the tyranny of small decisions is to develop and protect appropriate upper levels of decision making. Depending on the issue, decision making may be appropriate at a local, state, country or global level. However, organisations at these levels can entangle themselves in their own bureaucracy and politics, assigning decisions by default back to the lower levels. Political and scientific systems can encourage small decisions by rewarding specific problems and solutions. It is usually easier and more politic to make decision on individual tracts of land or single issues rather than implementing large scale policies. The same pattern applies with academic science. Most scientists are more comfortable working on specific problems rather than systems. This reductionist tendency towards the small problems is reinforced in the way grant monies and academic tenure are assigned.
Odum advocates that at least some scientists should study systems so the negative consequences that result when many small decisions are made from a limited perspective can be avoided. There is a similar need for politicians and planners to understand large scale perspectives. Environmental science teachers should include large scale processes in their courses, with examples of the problems that decision making at inappropriate levels can introduce.
* Diner’s dilemma
* Free rider problem
* Race to the bottom
* Social dilemma
* Social trap
* The Paradox of Choice: Why More Is Less
* Tragedy of the commons
1. ^ a b Kahn, Alfred E. (1966) “The tyranny of small decisions: market failures, imperfections, and the limits of economics” Kvklos, 19:23-47.
2. ^ a b c d e f g h i j Odum WE (1982) “Environmental degradation and the tyranny of small decisions” BioScience, 32(9):728-729.
3. ^ Burnell, P (2002) “Zambia’s 2001 Elections: the Tyranny of Small Decisions, Non-decisions and ‘Not Decisions'” Third World Quarterly, 23(3): 1103-1120.
4. ^ *Bickel WK and Marsch LA (2000) “The Tyranny of Small Decisions: Origins, Outcomes, and Proposed Solutions” Chapter 13 in Bickel WK and Vuchinich RE (2000) Reframing health behavior change with behavioral economics, Routledge. ISBN 9780805827330.
5. ^ Garrett Hardin, “The Tragedy of the Commons”, Science, Vol. 162, No. 3859 (December 13, 1968), pp. 1243-1248. Also available here and here.
6. ^ Baylis J, Wirtz JJ, Cohen EA and Gray CS (2007) Strategy in the contemporary world: an introduction to strategic studies Page 368. Oxford University Press, ISBN 9780199289783
7. ^ a b c Kahn AE (1988) The economics of regulation: principles and institutions Volume 1, pp 237–238. MIT Press. ISBN 9780262610520
8. ^ Thucydides (ca. 460 B.C.-ca. 395 B.C.), History of the Peloponnesian War, Book I, Sec. 141; translated by Richard Crawley (London: J. M. Dent & Sons; New York: E. P. Dutton & Co., 1910).
9. ^ Aristotle (384 B.C.-322 B.C.), Politics, Book II, Chapter III, 1261b; translated by Benjamin Jowett as The Politics of Aristotle: Translated into English with Introduction, Marginal Analysis, Essays, Notes and Indices (Oxford: Clarendon Press, 1885), Vol. 1 of 2. See also here, here, here or here.
10. ^ Mun T (1664) On obtaining a positive balance of trade by importing raw materials Chapter in England’s treasure by forraign trade.
11. ^ Capital and Interest by Eugen von Böhm-Bawerk London: Macmillan and Co. 1890, trans. William A. Smart, 1890. Library of Economics and Liberty (Econlib)
* Haraldsson HV, Sverdrup HU, Belyazid S, Holmqvist J and Gramstad RCJ (2008) “The Tyranny of Small Steps: a reoccurring behaviour in management” Systems Research and Behavioral Science, Jan-Feb, by
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