So much of the debate surrounding climate change seems to hinge on questions of causation. In particular, the two principal causation questions of interest are:
- Is the anthropogenic emission of carbon dioxide the cause of global warming?
- Is the global warming the cause of the current incidence of extreme or environmentally damaging weather-related events?
The stock response to the first question is to say that anthropogenic emission is a cause to a certain extent, but with the extent theoretically determined by scientific consensus. The stock response to the second question is to say that we cannot directly attribute any single weather event to global warming but we can say by how much the risk of such an event has increased.
In this article I do not intend throwing my hat into the ring with respect to any of the arguments that have taken place, but I do note that many such arguments seem to be hampered by the fact that those involved will often appear to be treating the concept of causation differently when they state their case. The result is that many such arguments are doomed to be unresolved as individuals continue to argue in circles. For that reason, I thought it might be an idea to present here a brief primer on the subject of causation and its relevance to the matters in hand.
Don’t worry. I do not intend boring you with a dissertation on the history behind the philosophy of causation. Instead, I will attempt a more pragmatic discourse by concentrating upon the nature of causal questions and what is required in order to answer them. None of this will actually require me to come up with a definition of causation – which is a good thing, because no-one has yet agreed upon one.
The questions I have in mind include the following:
- What will happen if I do this?
- Why did that happen?
- To what extent can attribution be made to a single precursor when there are multiple precursors to an event happening?
- Is a given precursor necessary and is it sufficient?
- What should my policy be, given my current understanding of the causation of events and the likely outcome of any interventions?
The Limitations of Data and Probabilities
The traditional approach towards answering such questions is to look for patterns within data and from them infer associations that could be causative. The central assumption here is that if the probability of observing Y is increased by observing X, then X may be posited as a causal agent for Y. In the language of conditional probabilities, X is a cause of Y if:
P(Y|X) > P(Y)
Of course, one can immediately see the difficulty with this approach. Simply observing a correlation between X and Y does not prove a causal link. In fact, the same effect might be observed if a common causation, Z, had been driving trends in both X and Y irrespective of any causal links between the two. In such situations, Z is said to be a confounder. To circumvent this problem, one compares situations in which Z is constant (i.e. one conditions upon Z) to see if the effect persists, i.e.
P(Y|X, Z=k) > P(Y, Z=k)
However, this rather raises the question as to how one could possibly know that all the potential confounders have been identified. Furthermore, whenever one conditions upon a potential confounder, one runs the risk of holding constant an important causal agent in order to focus upon a relatively unimportant one. Such a focus will have the effect of exaggerating the importance of the agent under investigation. The fact is, one can observe correlated probabilities until one is blue in the face but one will never properly tease out the causal story by doing that alone because causation isn’t fully captured by them and it never will be.
This obsession with observing correlated probabilities as the basis for inferring causation has been a problem for many years. Until relatively recently, probability had been the only game in town by which uncertainty may be analysed and so it is little wonder that its position as the sufficient concept behind causation has been inviolate. However, in the last decade advances in the fields of AI and machine learning have provided important insights regarding what information and concepts are required to enable causal thinking. And the most important insight is that one cannot think causally without having a causal model that is founded on an ability to conjecture upon the consequences of interventions and the implications of a counterfactual history. It is no good making field observations and trying to infer intervention, one has to explicitly model the intervention and then analyse the outcome in terms of altered observation. Only then can one talk about causation.
Causal Inference – The Very Basics
In order to address causal questions one first has to construct a structural causal model (SCM). A SCM can be formalised in many ways, but the most accessible and intuitive is the causal network, in which arrows are used to indicate a direction of influence. For example, take the following:
X –> Y –> Z
This is a simple network demonstrating that X is a cause of Z, mediating through Y. Another simple construct might be:
X <– Z –> Y
In this case Z is a confounder providing a common cause for X and Y, and whilst X and Y are associated they are not causally linked. This is known as a fork. Another simple construct might be:
X –> Y <– Z
In this case X and Z are both causal factors for Y. This is known as a collider.
It should not be difficult for the reader to imagine that some quite intricate networks could be constructed using a combination of mediators, forks and colliders. However, it is important to note that the result is only a model, sharing all of the simplifications and assumptions that any model has. Be that as it may, once one has such a framework in place, and data has been collected to put flesh on the relationships (i.e. data that indicates the probability rule or function that specifies how Y varies with X) one is then in a position to ask causal queries and see what answers are provided by the model. These queries fall into three categories:
Here one asks what would be the expectation of observing Y given that X has been observed. These questions can be answered by simply referencing the conditional probabilities linking the two variables, i.e. P(Y|X). To that extent, causal networks are similar in purpose to Bayesian belief networks.
Here one asks what would be the expectation of observing Y following an intervention in which X is forced to take on a particular value. Formally, this is expressed by applying the so-called do-operator, i.e. one determines P(Y|do(X)). These are basically questions of prediction. If X is a causation of Y then one would expect P(Y|do(X)) > P(Y). If this condition is not met then we need to rethink our causal model. For example, Y could be the observation of a cure and do(X) could be the mandated administration of a drug. If the condition is not met, then the drugs don’t work. The purpose of the do-operator is to preclude influences that could act as confounders with respect to X and therefore confuse the issue.
Here one accepts the observation Y but conjectures upon how it might otherwise have been with counterfactual values of X. This enables one to explore the broader implications regarding causation. For example, knowing the efficacy of the drug one can imagine withholding treatment in order to see what impact that would have in the context of other posited causal links. As with intervention, the query is graphically equivalent to removing arrows of influence and setting node values to posited values (in this case counterfactual ones).
The detailed mathematics and methods behind the above analyses need not concern us here. Suffice it to say, the game is all about determining the extent to which nodes within the network are ‘listening’ to others, i.e. does changing the value of the first alter the second. If there is such an ‘information flow’, then there is a causation between the nodes, even if they may appear remote within the network. It is worth emphasising that the same cannot be said of a Bayesian belief network since there are no assumed directions of influence encoded into such a model – new probabilities may propagate as a result of updated information but no causal inference may be drawn from such updating.
The Importance of the Counterfactual
Of the three basic forms of causal investigation (associational, interventional and counterfactual) those premised upon the counterfactual are perhaps the most insightful. Indeed, the central importance of counter-factuality is captured in a definition of causality offered by the philosopher, David Hume in 1748:
“We may define a cause to be an object followed by another, and where all the objects, similar to the first, are followed by objects similar to the second. In other words, where, if the first object had not been, the second never had existed.”
This is something of a hybrid definition since it starts out by stressing the importance of regularity (which, as I have explained, could be a spurious correlation) before then introducing the much more impressive evidence of the counterfactual. The cock crowing can appear to cause the sunrise, but one has to imagine the cock remaining silent before drawing any conclusions. In fact, it is this ability to imagine the counterfactual that sets the human race apart and enables its capacity for causal reasoning.
With a SCM, one can model the counterfactual simply by altering the values associated with a causal agent to see what the impact is. This is precisely what happens when climate models are re-run with anthropogenic emissions removed, in order to see how a prediction or retrodiction changes. The difference is interpreted causally, and there is nothing wrong with that. However, there are two important details regarding the modelling of the counterfactual that need to be mentioned here.
Putting Models on a Witness Stand
The first detail I have in mind was hinted at when former IPCC lead author, Professor Robert Muir-Wood wrote the following:
“Environmental Lawyers are following the attribution studies with great interest. If you can show that an event has doubled in probability, it may be possible to find some greenhouse gas emitters on whom to pin liability. But would the evidence withstand courtroom cross-examination and questions such as: Who exactly built this climate model? How do you know it is reliable?”
That is indeed a very good question, which many sceptics suspect should be answered in the negative. The problem with such attribution studies is that they are premised upon models that are notoriously compromised in their role as material witness. If one turns a blind eye to their structural uncertainties one can confidently draw causal inferences by playing the counterfactual game. But is it wise to turn a blind eye to structural uncertainty in a structural causal model? If one is going to evaluate as one would in a legal case, then one must forensically examine the evidential weight being offered before making a judgement. This detail often seems to be conveniently overlooked by those who rely heavily upon the credibility of attribution studies. Such studies carry a great deal of scientific kudos, but one has to wonder what a good lawyer could do in a courtroom.
Causality and Culpability
The second detail also has a legal dimension. In law there are two concepts that are important when deciding an individual’s culpability: the probability of necessary cause and the probability of sufficient cause.
In causal inference, the probability of necessary cause is measured by calculating the Probability of Necessity (PN). It relates to the legal expression ‘but-for causation’ since it expresses the likelihood that a known outcome would not have happened were it not for the defendant’s actions. For example, the defendant shoots at the victim and the victim dies from the resulting bullet wound. Here PN is high since it is highly likely that the victim would still be alive were it not for the shooting (i.e. the shooting was necessary for the death to have occurred).
In causal inference, the probability of sufficient cause is measured by calculating the Probability of Sufficiency (PS). It relates to the legal expression ‘proximate cause’ and expresses the likelihood that the defendant’s actions would lead to the known outcome. For example, suppose that the defendant had shot and missed, encouraging the victim to flee into the street, only to be knocked down by a herd of stampeding camels that just happened to be passing by. Here PN is still high (no shot means no fleeing) but PS is low, reflecting the fact that the direct cause of death was very unlikely and had very little to do with the defendant’s actions (it’s the camels wot dunnit). A high PN would normally result in a conviction, but not when combined with a low PS. Of course, in our example the PS might have been a lot higher had the incident taken place next to a busy motorway and no camels were involved.
The reason why I’m telling you all of this is because the probability of necessity (PN) and probability of sufficiency (PS) have a great deal to do with attributions of specific weather events to climate change. Take, for example, the following attribution statement made by Myles Allen and Peter Scott of the Met Office in the wake of France’s heatwave of 2003:
“It is very likely that over half of the risk of European summer temperature anomalies exceeding a threshold of 1.6oC is attributable to human influence.”
This statement (essentially a quantification of the Fraction of Attributable Risk (FAR)) relates to the probability of necessity, since it focuses on the climatic trends that provide the context for the weather experienced that year. It is saying that a ‘shot was fired’, and without it the possibility of the heatwave would have been diminished significantly. However, it wasn’t the climate that killed, it’s the weather wot dunnit. When one looks at the same problem from the perspective of the weather conditions, contingent as they are on several factors that have nothing to do with levels of CO2, the probability of sufficiency is actually very small – it takes an awful lot more than the anthropogenic influence to create incidents such as the French heatwave. To put figures to this, a study conducted by Alexis Hannart of the Franco-Argentine Institute on the Study of Climate, using the structural causal modelling techniques outlined above, led to a determination of PN=0.9 and of PS=0.007. There is not a court in the land that would convict with such figures.
The fact that causality has this duality (probability of necessary cause and probability of sufficient cause) leads to many differences of opinion when attribution statements are discussed, with the alarmed usually focusing upon PN and sceptics focusing upon PS. Worse still, the individuals concerned are often unaware that this is the true nature of their dispute. Even when the science is agreed upon, the conclusions can look very different depending upon which facet of causality represents the major concern. So who is right and who is wrong?
It’s All About Policy
So far I have discussed the issue as if it were a case of providing proof beyond reasonable doubt for each individual case. However, this is not really the issue. Instead, one should be looking at the long-term risk and establishing policies to manage that risk. Seen in this light, PS=0.007 still looks very significant. Even though it stresses the relatively minor role played by climate in a specific instance, the dice is still loaded in such a manner that the risk of such an event increases significantly when longer timescales are considered. And it is this long-term risk that drives policies such as those required for insurance: the fewer times we shoot our gun in public spaces, the less we have to insure against the habits of passing camels. The reality is that both PN=0.9 and PS=0.007 are significantly large from the point of view of politics and risk management. As Hannart put it:
“PS is the appropriate focus for the planner when assessing the future costs that inaction will imply, but PN is at stake when assessing the future beneﬁts of enforcing strong mitigation actions. Policy elaboration requires both sides of this assessment; thus both PN and PS are of interest here.”
Even so, one cannot help but suspect that the reason why the climate concerned seem so obsessed with PN is that it provides for bigger numbers, and bigger numbers are more scary, aren’t they? Well, they certainly are if one ignores alternative big numbers. For example, when analysing causation relating to bushfires, the PN for the climate change contribution might look impressive, but what about the PN values associated with negligent forest management, or trends in arson? In fact, forget about their PN values. Think about the PS values. When it comes to starting bushfires, there is nothing quite as sufficient as a lighted match!
So the answer to my question as to who is right and who is wrong would be that this is the wrong question to ask. A much better question would be the one asked by Professor Robert Muir-Wood when he drew attention to the question of model reliability. After all, as Judea Pearl, inventor of Bayesian belief networks and father of modern causal inference had this to say about the climate models:
“Though they are excellent at forecasting weather conditions a few days ahead, they have never been verified in a prospective trial over century-long timescales and so could still contain systematic errors that we don’t know about.”
Thus speaks possibly the world’s leading expert on causal inference.
And then, of course, there is the old chestnut regarding the incalcitrant uncertainty over ECS. But that’s quite another story…
I think I should point out that the Hannart study seems to take a different line to the one I have taken regarding the relative importance of PN and PS in a court case. Hannart states that a high PN will always result in a prosecution irrespective of the PS value. However, in my view, the example he gives only works because there are no other causal factors involved that could have caused the outcome; the PS in his example is low purely because the sole possible causation was actually improbable. In the weather event attribution case, there are multiple causations to consider, so I stand by my assertion that a high PN would not be sufficient to convict. Even if mankind is guilty of creating the climatic conditions that make such weather events more likely, it would still be inappropriate to convict for causing a specific weather event if there are many other uncertain factors that were necessary and they have little or nothing to do with man’s influence.
Perhaps the real issue here is the probability of necessary and sufficient causation (PNS) which is defined as the probability that Y would have occurred in the presence of X, and that Y would not have occurred in the absence of X. That said, when it comes to heatwaves, I suspect that PNS may still be sufficiently high as far as some analysts are concerned since local factors may play a relatively minor role.
Many thanks for this. I’m incompetent to comment on the mathematical argument, but the study you link to by Hannart and Pearl provides a clear exposition of the maths, and I promise to read it carefully.
The choice of Allen and Stott on the 2003 French heatwave deaths as an example of the difficulty of attributing causes is a case of shooting fish in a barrel for reasons that have nothing to do with the mathematical complexity you outline. The following IPCC report (AR4 or 5?) pointed to climate change as being a likely cause of the heatwave deaths, quoting two sources, one being a paper by the French medical expert who blew the whistle on the scandal, and the other being the official report by the French Senate. The first was entirely irrelevant, and seems to have been chosen purely because it was the only article which he had written in English, and the second placed the blame for the deaths firmly on failings of the health system. (everyone on holiday in August, so no-one available to sign cheques to pay for emergency ad campaigns etc.) Quoting sources that contradict your conclusion, in the hope that no-one will check them, seems tantamount to fraud.
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Thanks very much for your comment. I was beginning to fear that I would be the first person in CliScep history to score ‘null point’ on the comments board.
I think the point that you have made is very central to one that had been hinted at by my article. I would have been more explicit but the article was already getting a bit long, so I will be more explicit now:
When the IPCC were claiming that the French heatwave was caused by global warming they should have been clearer that they were only saying that the probability of necessity (PN) was high. There were other factors to consider that actually leave the probability of sufficiency (PS) very low. This focus leads to a misleading picture. I don’t know whether this is done knowingly or whether it simply reflects that most climate scientists are still well behind the curve when it comes to applying modern causation theory (unlike epidemiologists, by the way). However, perhaps more importantly, there is a vast difference between causing a heatwave and causing deaths related to a heatwave. To analyse the causation of the latter requires a much more extensive causal modelling that the climate alarmed seem neither qualified nor motivated to undertake. Therefore, the even lower probabilities of sufficiency that arise out of such an extended analysis are simply kicked into the long grass. And yet, as you point out, the IPCC will glibly cite studies that relate to incidences of death, assuming that the reader is not interested in the sleight of hand that has taken place. The climate alarmed seem to have the following simple model in their heads:
Anthropogenic emissions –> Global warming –> Heatwaves –> Deaths
And that is the model they want others to take on board. Nobody is supposed to look too deeply at the causal coefficients linking the mediators or worry about the absence of confounders in this model because that would weaken the case for the actions proposed. All that they need in order to justify their call for action is to allude to the high PNs and say that getting rid of anthropogenic emission deals with them by killing off the chain at source. From a risk management perspective, this is called risk avoidance (as opposed to risk mitigation). It is a valid option, but it is not always the most practicable. Sometimes it is better to focus on PS values and look towards ways of coping with the long-term risk. Maybe this is the real reason why sceptics make arguments that in effect draw attention to the low PS values whilst the alarmed are still ramming high PNs down the public’s throat.
And yes, I would strongly recommend that readers look into the Alexis Hannart study.
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Like Geoff I don’t do the maths, but I if I am being told something, I like to see if it is really happening.
In climate publicity we are told the basic truth is that CO2 is heating the planet, yet when I look at the data from official sources I find that CO2 isn’t driving temperature upwards, as in for example, CET has hardly moved in the last 30 years. Pierre Gosselin has a recent post showing the same thing with European datasets: https://notrickszone.com/2020/03/13/despite-mild-winter-europe-february-mean-temperatures-show-no-warming-over-three-decades/
When I chart annual changes in Mauna Loa CO2 against annual changes in CET, there is no correlation, the relationship is random, not causal, even going back 60 years to the start of the M Loa data. Therefore two values can rise over a similar period but without one being necessary for the other to exist.
Jamal Munshi has spent some time on exploring relationships like this:
THE CORRELATION BETWEEN EMISSIONS AND WARMING IN THE CET
JAMAL MUNSHI https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2956179
“A comprehensive detrended correlation analysis of the daily mean Central England Temperature (CET) series for each calendar month against fossil fuel emissions for the 245-year study period 1772-2016 is presented. Time scales of 10, 20, and 30 years were tried each at four different time spans ranging from 60 to 245 years at all possible locations within the overall study period. The results do not show a relationship between emissions and warming that can be interpreted in terms of the theory of anthropogenic global warming and climate change (AGW). The finding is inconsistent with the proposition that warming in the CET data can be related to emissions.”
When I chart annual changes in emissions of CO2 against annual changes in Mauna Loa data they do not correlate (as I said I don’t do maths, but visually they are all over the place), Munshi looked at this also:
“The IPCC carbon budget concludes that changes in atmospheric CO2 are driven by fossil fuel emissions on a year by year basis. A testable implication of the validity of this carbon budget is that changes in atmospheric CO2 should be correlated with fossil fuel emissions at an annual time scale net of long term trends. A test of this relationship with in situ CO2 data from Mauna Loa 1958-2016 and flask CO2 data from twenty three stations around the world 1967-2015 is presented.
The test fails to show that annual changes in atmospheric CO2 levels can be attributed to annual emissions. The finding is consistent with prior studies that found no evidence to relate the rate of warming to emissions and they imply that the IPCC carbon budget is flawed possibly because of insufficient attention to uncertainty, excessive reliance on net flows, and the use of circular reasoning that subsumes a role for fossil fuel emissions in the observed increase in atmospheric CO2.”
Circular Reasoning in Climate Change Research 7 Mar 2018 Jamal Munshi
“Circular reasoning is a logical fallacy in which research design and methodology as well as the interpretation of the data subsume the finding. This fallacy can be found in published research and it is more common in research areas such as archaeology, finance, economics, and climate change where the data are mostly time series of historical field data with no possibility for experimental verification of causation. In biased research of this kind, researchers do not objectively seek the truth, whatever it may turn out to be, but rather seek to prove the truth of what they already know to be true or what needs to be true to support activism for a noble cause (Nickerson, 1998).”
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The references to Munshi’s work mentioned by Dennis point to the error in the most basic casual assumption in this AGW discussion. If changes in our emissions do not change the atmospheric content of CO2 they cannot be causing it to rise but the IPCC assumes the entire rise is human caused. Harde, Salby and Berry have addressed the quantification of our additions to atmospheric CO2 and have been ignored, ridiculed and driven out of work for their contributions. The ubiquitous attribution studies conclude we are somewhat culpable for every extreme weather event while ignoring the lack of attribution in the first leg of the hypothesis. Their PN should be 0.0.
Thank you for commenting.
In much the same way that you might demur from discussing the mathematical theory behind causal inference, I would wish to demur from discussing the science of CO2 emission. I simply have not studied it enough to comment upon the details of your own comments.
I will say just this. Modern causal inference theory has taught that correlation will never enable us to get to the bottom of a causal enquiry. The world will take a long time to catch up on this idea, if ever.
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I’ve added a postscript to the article since I note that the Hannart study has a different take on the legal implications of a large PN combined with a low PS value. I’m no lawyer, so perhaps Hannart is right. But, there again, as far as I am aware, Hannart hasn’t studied law either. In fact, I think we have both got a valid point to make, despite the apparent contradiction.
Attribution it’s a, well you know, …’For want of a nail a kingdom was lost…'[
That’s a very valid point. When these causal networks are constructed, there are two sources of uncertainty that can seriously undermine confidence in the answers they give to causal queries. Firstly, there are the uncertainties associated with the probability rules and functions used to define the influence between any two nodes. Secondly, there is the structural uncertainty relating to whether there are any missing nodes in the network. In both cases, it is in the nature of networked models that small uncertainties can have a large impact on the reliability of model output. Just ask the epidemiologists.
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John, as promised I’ve now found time to read (and appreciate) this article in depth, rather than simply skimming it. I’ve had a busy day (food purchased and successfully delivered – left on doorstep! – to 89-year old father-in-law, not stopped by police en route), so have just read this now. I’d like to reflect on it before commenting further in my capacity as a lawyer, (though NB one who studied criminal law 38 years ago, but who never practised it, and who is now retired), so will revert it in due course.
I’ll come back to this later, but for now a useful link, from which I’ve reminded myself of half-forgotten law:
“Causation refers to the enquiry as to whether the defendant’s conduct (or omission) caused the harm or damage. Causation must be established in all result crimes. Causation in criminal liability is divided into factual causation and legal causation. Factual causation is the starting point and consists of applying the ‘but for’ test. In most instances, where there exist no complicating factors, factual causation on its own will suffice to establish causation. However, in some circumstances it will also be necessary to consider legal causation. Under legal causation the result must be caused by a culpable act, there is no requirement that the act of the defendant was the only cause, there must be no novus actus interveniens and the defendant must take his victim as he finds him (thin skull rule).”
There’s more detail at the link.
That’s criminal law, of course. The question of whether anyone could successfully be sued over climate change, as a matter of civil law, involves different tests, and I’ll return to that later.
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Thanks for that. You’ve provided just the sort of insights that I was looking for. In particular, your mentioning of novus actus interveniens led me to find the following:
Within the above one can find the following passage:
“A requirement for an act or omission committed after the initial wrongdoer’s act to constitute a novus actus is that the secondary act was not reasonably foreseeable. If the subsequent event was reasonably foreseeable at the time of the initial wrongful act, it is not to be considered as a novus actus capable of limiting the liability to be imputed on the initial wrongdoer.
A novus actus is not confined to either factual or legal causation only, and can interrupt the causal chain at either point. In respect of factual causation, a novus actus interrupts the nexus between the wrongful act of the initial wrongdoer and the consequences of his act to such an extent that it frees him of the liability of his actions. However, when assessing novus actus in respect of legal causation, regard must be had to the aspects of policy, fairness, reasonableness and justice in order to determine whether liability for the initial wrongful act can still be imputed to the initial wrongdoer, and whether the causal chain has been broken. A novus actus therefore disrupts the “directness” aspect of the initial act and the subjective test of legal causation cannot be fulfilled.”
So I guess the relevance of low Probability of Sufficiency (PS) values is that it bears upon what can be reasonably foreseeable. So, for example, whilst specific incidences of climate change induced storm damage could not be reasonably foreseen, storm damage caused sooner or later, can be.
And I trust all is well with your father-in-law now.
John, yes, all well with my father-in-law – thanks for asking.
So far as causation is concerned with regard to criminal liability, the concept of novus actus interveniens does seem to be critical. Assuming (and to my mind it’s a big assumption) that the Courts could be induced to accept that anthropogenic GHG emissions on a sufficiently large scale could be laid at some business’ or government’s door as a culpable act that led to, say, Australian bush fires, then an easy line of defence would be individual acts of arson as novus actus interveniens. Where it would get much more interesting from a legal point of view would be whether an act of omission could constitute novus actus interveniens – say a “culpable” failure to clear dead brush, which in turn made fires much worse than they would otherwise have been.
I’ll give this some thought, and will also revert to the question of remoteness in civil negligence claims in due course (I’m being distracted by other stuff this evening).
Anyway, thanks for turning my mind back to long-forgotten concepts, and for encouraging me to think a little harder about things! Remoteness, self-evidently, I think, is the question of whether a claim for damages can be founded even when in principal liability can be established, due, essentially, to the consequences of the negligent act being too remote to be reasonably foreseen, and therefore effectively is to do with your Probability of Sufficiency point.
I’ll try to find some useful links to express the point more clearly and with greater legal precision than I’ve just done.
Regarding remoteness in negligence cases, here’s a link from the same source as before:
I think that the test is drawn pretty broadly, and if liability could be established in principle (which in this context is, IMO, the difficult part of any claim) then the potential for damages could be enormous. Given the enormous resources devoted to laying everything and anything at the door of man-made climate change, claimants would have a head start in claiming that any loss was foreseeable, I fear.
I’m quite comfortable with the idea of an omission serving as a novus actus (the website I linked to provided the example of a person dying following a car crash. The culpability of the individual causing the crash was mitigated by the fact that subsequent medical negligence had contributed to the victim’s demise). So I think both of the bushfire examples you gave are absolutely germane.
As for pinning harmful events on the acts or omissions of a specific organisation, I think a particular difficulty there would be the problem of joint and several responsibility, wherein the PN values for individual parties starts to drop. For example, can it be demonstrated that the acts of a specific oil producer were necessary for an outcome, or can necessity only be demonstrated in regard to the aggregated effect of several parties’ actions (I’m thinking of the firing squad example, where any single shot fired cannot be deemed a necessary cause of death because the other shots would suffice). The PN value for AGW may be high but that for Exxon much, much lower.
We should also keep in mind that the oil companies act on their customers’ behalf as well as shareholders. Does the culpability extend to all those who benefited from the supposedly nefarious act or omission?
I also wonder whether we need to ask if a novus actus can be attributed to a non-intentional agent such as the weather, i.e. we can’t actually put the weather in the dock, so does that mean we have to take a different view regarding those who we can?
Foreseeability? That’s a difficult one. Long term risk is easier to deal with because even low values for PS imply foreseeable risk. However, specific weather events are not so foreseeable, and so culpability attached to such events would surely be more problematic.
But above all else, I question whether the prime witness for the prosecution (climate models) can possibly stand up to the sort of cross-examination that one might expect to receive from a good barrister. I doubt it.
John, I’m very much inclined to agree with your line of reasoning.
However, I’d like to stray from the point a bit, though I think iwhat follows is tangentially relevant.
When I was an articled clerk in the mid-late 1980s, I worked for a Newcastle upon Tyne law firm which acted for the NUM and NACODS. They built a successful arm of the firm in pursuing industrial deafness claims against the NCB, on behalf of deaf miners. To our minds now it seems obvious that working with noisy machinery day in day out without ear defenders, will cause deafness – it is reasonably foreseeable. For an employer to fail to provide an employee with ear defenders while exposing them to excessively noisy machinery will today clearly found a case in negligence if the employee develops deafness as a result.
Back in the early 1980s, however, the situation wasn’t quite so straightforward, at least with historic claims. Eventually it was decided in Thompson v Smiths Shiprepairs (North Shields) Ltd  that 1963 is generally to be regarded as the date by which the harmful effects of excessive noise were
foreseeable. In large part this was because in June 1963, the Ministry of Labour published Noise and the Worker, a guide which advised employers that if they were aware of any problems with noise then employees’ exposure ought to be reduced and, where possible, hearing protection provided. The guidance suggested that exposure to noise of 90dB(A) over the course of an eight-hour working day was dangerous.
At a personal level, the effect of this struck home one day when I was interviewing a very old ex-miner who had been brought to the NUM hall in Newcastle where we were vetting miners and ex-miners to see if they might have a valid claim. As I worked through his CV (in those days I rapidly developed a knowledge of the types and noisiness of mining machinery in different pits in different years when miners were undertaking specific jobs/roles) it became apparent that he’d retired in 1962, so would not have a claim. I dreaded breaking the news – he was such a nice old man, but completely stone deaf, and had it not been for the “date of knowledge” test, he would have had a very strong claim. He took it so well, and simply said something like “Ah well, never mind hinny, I’ve had a nice day out.”
But I digress. I do wonder whether the storm of propaganda seeking to link “climate chaos” to CO2 emissions isn’t a pre-emptive strike to lay the ground for a later claim, with the “public interest” claimant at some point in the future laying before the Court a host of “scientific” propaganda dating from the 1980s onwards, and saying “see, this was foreseeable since at least [insert date] – that’s the date of knowledge since all this was reasonably foreseeable, and the defendant is liable for everything that’s happened since then.”
Am I being too cynical?
I don’t think you are being cynical at all. I haven’t been following closely the recent efforts to indict oil companies, but the old ‘they knew all along and yet kept it secret’, argument seems to loom large in the legal machinations. This has always struck me as odd. It’s not like the tobacco scandal where the research was being undertaken by tobacco companies themselves, and they were keeping the results secret. The insider knowledge that the oil companies are supposed to possess is only the same stuff that is out there for all to see – and we are all at liberty to interpret it as we see fit. There is no damning and incontrovertible evidence that has been swept under the carpet. There is, however, a social norm of acceptance, and I suspect it is that which will form the basis for judgement – not any hard and fast scientifically established facts. The promulgation of the ‘scientific propoganda’ is all part of the establishment of that social norm. It’s not a case of ‘you continued even after you knew it to be damaging’, so much as ‘you continued even after you knew that it was no longer approved of by society.’ What I do know is that future proceedings are probably going to involve a lot of tampering with the moral milometer.
I’ve been thinking a bit more about the foreseeability question and I’m beginning to share your concerns. Low PS values will provide little defence if the attitude taken is ‘you knew this would happen sooner or later’. That seems to represent a case for criminal negligence. Also, low PN values may also be of little use if the attitude taken is ‘you knew your efforts would combine with those of others, so you are all responsible.’ But it still seems wrong to me that cases relating to specific weather events could be settled on the basis of a hypothetical guilt, particular when the supposed miscreants were acting at the time in accordance with socially accepted standards of behaviour. And I keep coming back to the credibility of the witness. For example, climate models that are validated against the same criteria used for their calibration are no better than a witness that has been paid to give their testimony.
As a person who worked for those evil, all-knowing, oil companies during the critical 1980s and then went on to teach and train those tasked with finding and producing even more of the so-called climate-altering hydrocarbons, I refute any blame or culpability. In my defence, I place before the court, the countless benefits that my (and my many colleagues) contributed to society both in terms of product and as financial positives (to shareholders and to society in general). These benefits were predictable; the climate-changing negatives (if they exist) were not. Are the climate-changing positives (if they exist) being considered in my defence?
Other than the above, I plead insanity.
Next thing, you will be saying ‘I voz only following orders’. 🙂
Nevertheless, you make a good point. You wouldn’t have done your evil crime if society hadn’t put you up to it. If it pleases m’lud, I call witness A – the human race.
John and Alan
I’m far – very far – from satisfied that in an English Court anyone could be held liable for climate change and successfully prosecuted for it (on the – criminal – hand) or damages awarded against them (on the other – civil – hand).
I do, however, point out what I suspect might be the tactics of those who try to establish just that.
Mark. It would be patiently unfair if anyone could be held liable for climate-change damages, given that climate activists have clearly been responsible for criminal damage and obstruction, yet have had all charges repeatedly dismissed (or forgiven) by juries and judges. It would be one law for luvies and the climate pure, another for…(us?)
I’m happy to agree with you, but Alan’s point is also germane. All this talk of PN/PS values, proximate cause and novus actus interveniens may be overthinking things if courts are abandoning legal traditions in favour of green politicking. In the battle between logic and ethics it isn’t always clear what the outcome will be.
Thanks for this discussion which I only now discovered. The role of courts and legal argumentation has been an interest of mine, not because I have expertise (I don’t), but because alarmists are hoping judges will grant the victory of imposed decarbonization that politicians have failed to deliver. My readings come from US and Canadian sources, so derive from traditions differing from the UK but with some common origins.
Two of my posts are pertinent here. One goes into the US legal paradigm that applies when litigating liability for damages from medicines or workplace conditions upon those exposed. The approach to deciding causation gets at how lawyers try to cope with scientific data and statistics.
Another post discusses how some legal scholars are trying to catch up with the expansion of environmental law to force rulings on fossil fuel emissions. Basically, the judiciary is ill-prepared for the slew of cases mounted by climate lawyers.
Thanks for the links. At this stage I have only read the first article (very interesting) but I am already motivated to share some observations:
1) The Bradford-Hill criteria for deciding causative factors have been well-established since the days when a causative link was sought between smoking and lung cancer. However, they are a second-best substitute for a truly causative logic such as that provided by a Structural Causal Model (SCM). That is because they are only designed to address the associational properties of causal relationships. A truly causational analysis can only be achieved by also looking at interventional and counterfactual implications, and this can only be done using an SCM with its concomitant, causal inference calculus.
2) Another highly informative take on evidence-based decision-making can be gained by looking at the subject from the perspective of safety-critical systems engineering. Here, the basic objective is to create a formal safety case prior to introducing new systems, or modifications thereof, to ensure that acceptable levels of safety can be expected. I could write an absolute tonne on that subject – and one day I might. You have all been warned.
3) As with the concept of the scientific fact, the concept of scientific evidence derives from legal terminology (i.e. the law courts had already established the relevant concepts before the scientific revolution got underway). I am now tempted to write an article ‘A brief History of the Evidence’ to accompany my ‘Brief History of the Fact’.
Thanks John. If this leads you to expand on the above points it will be most illuminating. In the second article mentioned there is a link (which I had to refresh just now) to a paper subjecting IPCC to cross examination. Your reflections on that would also be of interest. An excerpt:
“This paper constitutes such a cross-examination. As anyone who has served as an
expert witness in American litigation can attest, even though an opposing attorney may
not have the expert’s scientific training, a well prepared and highly motivated trial
attorney who has learned something about the technical literature can ask very tough
questions, questions that force the expert to clarify the basis for his or her opinion, to
explain her interpretation of the literature, and to account for any apparently conflicting
literature that is not discussed in the expert report. My strategy in this paper is to adopt
the approach that would be taken by a non-scientist attorney deposing global warming
scientists serving as experts for the position that anthropogenic ghg emissions have
caused recent global warming and must be halted if serious and seriously harmful future
warming is to be prevented – what I have called above the established climate story. The
established story has emerged not only from IPCC AR’s themselves, but from other work
intended for general public consumption produced by scientists who are closely affiliated
with and leaders in the IPCC process. Hence the cross-examination presented below
compares what is said in IPCC publications and other similar work by leading climate
establishment scientists with what is found in the peer-edited climate science literature.”
“The point of this exercise in cross-examination is twofold. The first is just to run
a relatively simple check, as it were, on the claimed objectivity and unbiasedness of the
IPCC AR’s and other work underlying the established climate story. Do IPCC AR’s,
summaries and other work by leading climate establishment scientists seem to frankly
and openly acknowledge key assumptions, unknowns and uncertainties underlying the
establishment projections, or does work supporting the established story tend instead to
ignore, hide, minimize and downplay such key assumptions, uncertainties and
unknowns? To use legal terms, is the work by the IPCC and establishment story lead
scientists a legal brief – intended to persuade – or a legal memo – intended to objectively
assess both sides? The second and related objective of this Article is to use the cross
examination to identify what seem to be the key, policy-relevant areas of remaining
uncertainty in climate science, and to then at least begin to sketch the concrete
implications of such remaining uncertainty for the design of legal rules and institutions
adopted to respond to perceived climate change risks.”
The paper by Jason Scott Johnston is here:
Click to access UPennCross.pdf
“Such studies carry a great deal of scientific kudos, but one has to wonder what a good lawyer could do in a courtroom.”
I will read the Scott Johnston paper with relish!
I’ve found the following excellent paper for those wishing more information on the application of Structural Causal Models. In this instance, the models are being used to explore social and psychological causations:
Over at ATTP they have been discussing an Extreme Events Attribution (EEA) paper that Ken Rice appears to dislike:
Generously, he concedes that he may have mistaken the point of the paper and invites clarification from his audience:
“Of course, maybe I really just misunderstand what’s being suggested in this paper. If so, I’d be more than happy to have it clarified.”
I felt that the paper might make a lot more sense to the ATTP crew if they approached it from a structured causal analysis viewpoint, and so I posted a couple of comments (complete with embarrassing typo) to explain what I thought was the problem – No, I might as well say it: what I knew was the problem.
Now normally, my comments on ATTP are as welcome as a fart in a spacesuit, and the usual suspects do not waste a moment in their defence of the faith. But, strangely, this time they have greeted my contribution with a stony silence. No ‘LOLs’. No ‘Give me a break!’ No ‘Ooh the irony!’ No winking man emojis to indicate that they see behind my ‘uncheckable credentilaism’. Instead, I have been treated to a fascinating discourse on the deconstruction of Shakespearean sonnets, followed by ‘Okay, now let’s talk about COVID instead’. This I find very odd because, having received the clarification that he had sought, I would have thought that at least Ken would have had something to say about it.
Watch this space. They may still be organizing a belated counter-attack. I can’t believe that they have finally realized that their expertise on the subject is just not up to the job.
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Well, it took a third session of ground baiting, but I finally got someone to take the bait – Willard has written the following over at ATTP:
“I am not a fan of establishing causality of singular events in this context. Most climate scientists I know don’t go as far as to speak of the odds of event E to have occurred because of AGW. Yet that’s the kind of claim for which Judea’s causation calculus is designed. Before requiring climate scientists to abide by it, its proponents might need to reflect on why he still can’t sell it elsewhere.”
Now I have a dilemma. Do I remain silent and leave Willard to believe that his crude effort at convincing everyone he is already well ahead of the game on causation calculus has worked? Or should I point out how ill-informed and ignorant he appears to someone such as myself when he writes such stuff. If I do, that will only invite Willard to retaliate with his special brand of personal abuse and condescension.
For example, I am tempted to point out that, in this context, causation calculus isn’t actually designed to determine ‘the odds of event E to have occurred because of AGW”. In fact, in causation calculus there isn’t even a concept of ‘the odds of event E to have occurred because of…’ Instead there are two complementary concepts based upon the counterfactual:
a) Given that X and Y have happened, what is the probability that Y wouldn’t have happened if X hadn’t happened?
b) Given that neither X or Y has happened, what would be the probability that Y would have happened if X had happened?
And I am also tempted to point out that the first of the above questions is currently answered by climate scientists when they calculate the Fraction of Attributable Risk. In that respect ‘Judea’s causation calculus’, as Willard put it, is already central to EEA. Climate scientists are not being asked to abide by it, they are already doing half of it unwittingly. Furthermore, the second question is answered by climate scientists when they take a more ‘story line’ approach, analyzing causation at a regional level. Admittedly, this approach is more problematic and is controversial amongst EEA practitioners. Nevertheless, both approaches are required to complete the causal narrative.
And I am tempted to point out that the actual purpose that Judea Pearl had in developing causation calculus had nothing at all to do with demonstrating that there was such a thing as probability of causation. In fact, he was interested in re-introducing a concept of causation into statistics that goes beyond data-mining for correlations and one that can be applied in circumstances where a randomized control trial cannot, or should not, be used.
And I am tempted to point out that Willard failed to substantiate his remark regarding the failure to ‘sell’ the idea of causation calculus elsewhere. I find myself wanting to point out to Willard that Judea Pearl seems to be more than happy regarding its widespread application in epidemiology, economics and social science, to name but three. Yes, he is a bit disappointed that climate scientists have been a bit slow in following suit but maybe Pearl is not fully appreciating the technical difficulties that are encountered by climate scientists who attempt it. See, however, the Hannart paper I cite in my Brief Primer on Causation, of which Pearl is a co-author.
Finally, I am tempted to point out that Judea Pearl is the guy that gave the world Bayesian networks and has been awarded the Turing Prize in computer science. I dearly want to ask Willard if he really is expecting me to trust his judgement in preference to the world’s leading expert on causal analysis.
But, alas, I think I am going to have to give it a miss. My last foray over at ATTP was warning enough that I am not dealing with people who can hold a mature debate. So I will leave Willard in his blissful ignorance and move on, satisfied that I have answered my question as to whether there is anyone over at ATTP who knows anything about causation. The answer is ‘No’.
Meanwhile, Ken remains resolutely silent. Maybe he’s the guy after all.
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Prob’ly pearls before swine, John.
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Beth, perhaps a longer version of your Sermon on the Mount quotation would have been appropriate:
“”nor cast your pearls before swine, lest they trample them under their feet, and turn and tear you in pieces.”
I believe John is apprehensive about the last part.
Too true. What is it they say about wrestling with pigs in muck? I’m still in two minds, though. It should be possible to point out the errors in a deadpan manner. If I just stick to facts, maybe I’ll get away with it.
Meanwhile, I’m very sorry to hear about your ongoing problems with the damned virus. I have heard that hot weather is making breathing worse for sufferers. Maybe you will find some relief when the weather breaks down. If you visit Michael Rosen’s twitter you will see a number of people commenting upon the long-term effects of the virus. The general view is that this is an untold story that will eventually become a big deal as it becomes clear that the damage done to society cannot only be measured in terms of death tolls and economic carnage.
John Medicine dispensed in small doses perhaps?
Thank you for your concern.
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I’ve even composed my comment, yet I am still reluctant to post. I don’t think the comment is inflammatory but I suspect that all Willard will read is ‘Lay on Macduff”. The proposed comment reads as follows (Is there anyone out there thinks it is worth posting, or should I just let sleeping dogs lie? After all, no-one is paying me for this free tuition):
“Yet that’s the kind of claim…”
Not exactly. Whilst that may be the way in which people choose to express themselves, it isn’t actually a claim that enters into the calculus. See my comment at June 22, 8.09pm. When it comes to AGW and EEA, a calculus based upon two counterfactuals bounds the issue.
“…for which Judea’s causation calculus is designed.”
No. Causation calculus was designed to introduce into statistics a concept of causation that goes beyond data-mining for correlation. It also provides a technique that can be used when randomized control trials either cannot or should not be performed.
“Before requiring climate scientists to abide by it…”
No. No-one is requiring climate scientists to abide by it – they are already doing it of their own volition, albeit unwittingly. See my comment at June 21, 11.19am.
“…its proponents might need to reflect…”
No they don’t. They just need to read Judea Pearl’s ‘Book of Why’, in which he expounds at great length upon why an idea such as causal calculus might encounter considerable intellectual inertia within the field of statistics.
“…why he still can’t sell it elsewhere.”
No. In fact he has been very successful in ‘selling it’ to a number of disciplines including epidemiology, economics and the social sciences. Remember, this is the man who gave the world Bayesian networks. He is also a recipient of the Turing Prize for computer science. I suspect that he isn’t waiting to hear your opinions regarding his success in the field.
John I suggest one pearl at a time.
Feed them just one of your paragraphs, then assess the fallout before proceeding with the next
This would allow you to assess the biliousness of the response, but not give them too much rope to chew upon.
Serfs say ‘Publish’n be damned. 🙂
Serfs say, ‘Publish ‘n be damned!’
I think your advice is basically sound but, on this occasion, probably not sufficient. Even if I restrict my response to a critique of Willard’s opening sentence, there is already enough tension in the subtext to cause a hostile response. Basically, Willard has said, “John, you came on here thinking you were the big expert but I am actually quite underwhelmed.” To which I respond, “Well, my expertise has enabled me to discern that in your opening sentence you have managed one inaccuracy and one blatant mistake, so I see no basis for you to be underwhelmed.” It has already become a battle of egos. Maybe this is not a hill for me to die on.
Plant your flag deep and proud on that hill John. Egos be damned, it’s expertise that should win the day. Willard vs your knowledge and practical experience: it should be no contest.
I appreciate your support but you would have me kick a dung heap here. The only thing that is likely to happen is that I will get shit on my shoe and will have to live with an unpleasant odour that outstays its welcome. I went on to the ATTP site to try engaging in a useful debate. Nothing came of it, apart from Willard’s ill-informed response. If I felt that critiquing his effort would suddenly lead to the debate I seek, then I would. But you know as well as I do that ain’t gonna happen. I don’t actually like interacting with Willard. It isn’t intellectually fulfilling and it tempts me into playing silly buggers. If he is willing to arrogantly dismiss the work of a Turing Prize winner, I’m sure he isn’t going to be impressed by anything I have to say. So I am still of a mind to leave him to his self-amusement.
I’m sorry to disappoint you but I do feel that you are imagining a victory in an intellectual joust. If it looks to Willard like I have won such a joust, he will simply delete my comment. I know this from bitter experience. That, or he will respond with a meaningless, one-liner put-down that defies response. He’s done that once already in the debate (“That’s POMO”). He’ll just do it again.
John. Actually you have made your case here. Surely Willard must know this or will be informed of it?
The argument that now convinces me that you are doing he right thing is when you reasoned that, if you were perceived to be winning, the whole interchange would be removed. SO why bother? You’ve made your case here. Anyone who demurred can respond here.
Alan and Beth re. pearls and pigs:
“Education today is casting synthetic pearls before real swine.–H.L. Mencken
If I could activate the ‘like’ button, I would! Sometime I can, sometimes not. My computer is crazy. (
John, quite right. What was I thinking of? I was acting as an urger. (
Well, you can’t say I didn’t warn you. True to my word, I did not respond to Willard, preferring instead to restrict myself to expressing areas of agreement whenever I saw them. In that vein, I posted the following in response to someone calling themselves ‘Izen’:
‘The ‘CONCERNS’ which are expressed by the STS, pomo authors, for which as WIllard suggest we should offer our thanks, would seem to be that the focus on the role of AGW in changing the probability of extreme events that have a significant impact on life or health, is overriding the consideration of the role of human error and economic expediency in the impact of the weather related extreme events.’
Excellent. As I said in my comment at June 25, 1.13pm, “…if people were to read ‘The Cure for Catastrophe – How we can stop manufacturing natural disasters’, written by former IPCC Lead Author, Robert Muir-Wood, they might have more sympathy for these STS guys.”
All we need to do now is to understand:
a) That it is in the nature of causality that the modelling of such factors has to be treated as an extension of EEA.
b) That one would not expect the EEA community to do this, although their output is required and their involvement would be helpful.
c) That the modelling should take the form of a structured causal model (SCM).
d) That SCMs are not currently common practice within EEA.
e) That the SCM will be restricted to matters of physical causation. Matters of social justice are for others to consider.
f) That nothing in such modelling will alter the probability of necessity with respect to AGW but it will alter the probability of sufficiency as more and more human factors are included in the causal model.
g) That the motives of the STS guys needn’t concern us. All that should matter to us is that the causal model is complete.
h) To reduce the risks, actions should be considered that have the effect of reducing either the probability of necessity or the probability of sufficiency. The latter, in particular, will address anthropogenic factors supplementary to greenhouse gas emission.”
Unfortunately, Willard was prowling and pounced with:
“> All we need to do now is to understand:
As I said earlier:
If they want to push for another kind of framework, like John does here every season or so, then the onus is on them to make it float.
So I suppose by “we” you mean yourself?
Please report when you make progress with your framework sell.”
To which I replied:
Throughout this debate I have been fastidiously careful to avoid a confrontational tone, as I have learnt that such a tone is invariably counter-productive for me here. For that reason, I chose not to rise to your comment earlier saying “That’s POMO”. Nor did I succumb to the temptation of correcting your attempted dismissal of causal calculus (though, God knows, it was so error-strewn that it was crying out for someone to do it). I didn’t even rise to your accusation that I was simply trying to ‘reframe’ the problem, as usual. So I certainly will not be responding here to your latest provocation.
Now if you’ll excuse me, I need to get back to my meditation. Peace to all.”
WITHIN TWO MINUTES MY COMMENT HAD BEEN DELETED!
In the interests of moderation, I have felt it appropriate to withdraw the closing paragraph of this comment. I will re-express myself tomorrow in more temperate terms once I have calmed down.
You know that the moderation on my site is somewhat stricter than on other sites. We tend to delete comments that are just complaining about tone, or moderation, or – as Willard would put it – are playing the ref. If your response to that is to call someone a predictable, pathetic excuse for a man, it’s hard to then feel all that sympathetic.
‘t would be good if Willard played fair, seems winning by fair means or foul is the name of his climate ball game.
You are quite right. I should have simply pointed out that Willard’s ‘moderation’ was both pathetic and inexcusable and left it at that. As for your sympathies, you must understand that I have little use for them. You delude yourself in thinking you have ‘strict’ moderation. The words I would use are ‘tendentious’ and ‘cowardly’. How about adding the rule that criticisms should be substantiated rather than be flippant and arrogantly dismissive? That would be a far more legitimate use of moderation than the censoring of someone who is just registering his reluctance to respond to negativism.
My God you are deluding yourself if you think I would allow you to remove my complaint and then let you come onto my blog to repeat the offense.
Needless to say, this is the last commentary that will be allowed on this subject, and you needn’t worry about ‘moderating’ me again.
It seems to me that the problem with your justification for the deletion of John Ridgway’s comment at your site (“If your response to that is to call someone a predictable, pathetic excuse for a man, it’s hard to then feel all that sympathetic”) is that such response was posted here, and not at your site. The comment he posted at your site that was deleted seems to me to have been moderate and polite.
As I know from a foray at your site years back (when I vowed not to waste my time posting there again, unless for the sake of politely asking a question or making an anodyne comment that could not possibly offend alarmist sensibilities) you allow much worse from your supporters seeking to take down those who don’t agree with you.
It’s your site, and you may obviously moderate it as you see fit, but from where I’m standing, the moderation there does not seem to be consistent, and whether or not a comment is deleted seems to be as much (if not more) about whether it’s supportive or antagonistic to the whole CAGW viewpoint, and the arguments you and your supporters propose, as it is about whether or not a comment is offensive.
FWIW (which may not be much) that doesn’t seem to be much of a way to generate an intelligent discussion about the issues. The Conversation operates in much the same way, which is rather ironic, since a conversation seems to be the last thing they’re seeking.
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Your problems with Dr Physics are as old as the dialogues of Plato. Every time Socrates argues Gorgias or Protagoras into a corner they go off in a huff. But Plato never moderated their arguments away; he let them stand for all the world to see two and a half millennia later. Whereas Gorgias and Protagoras and the other Sophists excised any awkward comments from Socrates out of their works. See for example Protagoras’s “Techne Eristikon” or “the Art of Intellectual Wrestling.”
Well, actually, you can’t, because it no longer exists. None of the works of the Sophists exist, because no-one thought it worthwhile to conserve them. I wonder why?
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John. May I applaud your decision to post your comments at aTTP here. If they get deleted there, at least they survive allowing all to judge the merits (or otherwise) of the case.
I do however somewhat regret that you removed your last paragraph in your 28 Jun 20 at 3:50 pm post. Later reflection may have judged it intemperate, but it was your genuine response to what had happened to you. The genuinely funny part is Ken’s complaint about it as if it had been written on his own blog. At least it has caused the absentee to reappear and trip himself up.
My greatest regret is that I allowed myself to be goaded into losing my temper, because it feels as if I presented them with a minor victory. I think scientologists would learn a great deal from watching how Willard and Ken operate. I feel better for having admitted that I spoke out of turn, but I am unapologetic insofar as it was a genuine and justifiable emotional response. I think the real point to take away is that I visited Ken’s site to make what I believed to be a constructive and highly germane contribution. The response, at best, demonstrated a profound disinterest in what should have been of great interest to the forum and, at worst, resulted in unwarranted, snide remarks from an individual who resorted to censorship the moment he was called-out.
I will not be returning to ATTP — not because it would not be worth my while, but because I have concluded that the site itself is worthless.
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Here’s the thing: ‘I have high standards of moderation and so I delete comments that complain about tone’, says the man in a comment complaining about tone. The irony is that it is only because my standards of moderation do not match up to his ultra-high standards, that his comment was allowed to be shown here at all.
I think this spat neatly exemplifies how one’s working assumptions create blind spots. Assuming that his moderation is reasonable and fair, Ken interprets my reaction as being that of an unreasonable man undeserving of his sympathy. However, had his starting assumption been that I am a reasonable man deserving of his sympathy, my extreme reaction would then be evidence that his moderation was anything but reasonable and fair. It’s called prejudice and it allows for all sorts of indulgences and malpractices to go unchecked.
Incidentally, when I said that I would not be allowing further comment on this issue, I was only referring to those who would fall foul of my new-found appetite for moderating any contradiction. The rest of you can fill your boots 🙂
One effect of the lack of even-handedness in the application of moderation is that it is not possible to point out on ATTP’s forum when one feels that someone is being nasty or stupid, unless, of course, when you are on the ‘right’ side. This means that I have previously found it necessary to express such views over here at Cliscep. When doing so, I am quite aware that I use the rhetoric of disdain to admonish those who use the rhetoric of disdain. Willard and Ken believe that this is me being hypocritical because I am doing the thing that I am complaining about. What they do not appreciate, however, is that I am not actually claiming to live by higher standards. I have more than once expressed discomfort at having resorted to such rhetoric. But I don’t actually think that the rhetoric of disdain is the real problem. The problem is that, whilst the disdain is mutual, the rights to express it are not granted equitably at ATTP. By allowing Ken to post his complaint here, I hope that I am demonstrating that, in that important respect at least, I am not a hypocrite. Be that as it may, accusations of hypocrisy get us nowhere. It is not hypocrisy that is tiresome – it is allegations of hypocrisy.
I now hope to render this a historical problem for me, since I do not intend visiting ATTP anymore. After all, what worth is there in a forum that cannot see how focussing upon the logic of causality is relevant when discussing a paper that questions the scope of causal models?
Last night, quite out of the blue, I experienced a diarrheal efflux the had the thrust of a Saturn V rocket.
“Oh my, what could have caused that?” I found myself asking.
Straight away, I narrowed down the options to the three most likely causes: A virus, food poisoning, and climate change. A little internet searching was all that was needed to unearth the relevant science:
“Diarrhea is one of the major diseases linked with changing climate.”
Fortunately, as with my personal plight, the study’s abstract was full of crap but the ending was left open:
“Statistically significant correlation between diarrheal cases occurrence and temperature and rainfall has been observed. However, climate variables were not the significant predictors of diarrheal occurrence.”
Of course, the lesson of my article is that statistically significant correlation can’t usually settle the issue of causation. For that a counterfactual needs to be explored, such as asking what might have happened if I hadn’t eaten that house special jalfrezi the night before. Just how special had they made it?
Still, from an extreme gastric events attribution viewpoint, the curry may be to blame but climate change is still making such events more likely.
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John The link between your being struck down by gastric intemperance and climate change is fairly obvious. The former has long been known to be linked with anxiety and, all your concern about risk assessment and climate chaos must be taking its toll. Think about other matters; give yourself a break. If you lived in Norfolk you could think about other viruses like bird flu and the death of beloved flamingos.
No sh*t Sherlock, as they erroneously say.
It is bad enough when the BBC’s so-called climate disinformation specialists try to debunk by using a flawed causal argument, it is worse still when they also attempt to debunk by using the exact reversal of the same flaw. Here is the BBC’s Paul Kirkby suggesting that climate change is the cause of recent forest fires whilst ignoring its insufficiency in the outcome. Apparently, necessity is all that matters when it comes to causation:
And here is the BBC’s Marco Silva talking about green policies not being the cause of recent problems in Sri Lanka, whilst ignoring their necessary role in the outcome. So now sufficiency is all that matters when it comes to causation:
In both cases they make the basic error of thinking they can debunk claims regarding causality whilst they themselves use an incomplete conception of causation. It is even more galling to see that each uses a logic that flatly contradicts the other. Which is it to be guys? Necessity or sufficiency? It’s make your mind up time here.
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That piece by Marco Silva would – IMO – rate about 4/10 if handed in as homework by a 12 year old. So much for Climate Disinformation Specialists.
And yet he speaks highly of himself:
It’s never a good idea to mark your own homework.
Peer review John. He couldn’t find anyone else that low.
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John – wondered how long it would take you to comment on recent forest fires 🙂
ps – notice the BBC web post now add this (maybe been like that for ages & I never noticed) – “The BBC is not responsible for the content of external sites”
the piece by Marco Silva really buts any “right-wing US and UK media outlets and politicians, as well as climate-change sceptics” in our place as thick.
because he quotes “experts say” to back up his post.
the links he gives are more BBC posts, but the common link to the problem seems to be “People have been struggling with daily power cuts and shortages of basics such as fuel, food and medicines.”