Steve ( @[email protected] )

The Covid scandemic aligned exactly with the global 5G rollout. Brain fog, fatigue and the loss of sense of taste amd smell are all symptoms of EMF poisoning. What are they planning this time just as 6G is being rolled out ? https://t.co/5DqNTfU6M5

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Steve ( @[email protected] ) @g0lfp

11 days ago · Southam

@DrChrisParry Steady!

Steve ( @[email protected] ) @g0lfp

12 days ago · Southam

@melindiscott

Steve ( @[email protected] ) @g0lfp

12 days ago · Southam

@melindiscott Lonely.

Steve ( @[email protected] ) @g0lfp

13 days ago

@ladyslabour Jolly good!

Steve ( @[email protected] ) @g0lfp

15 days ago · Lake

@melindiscott In view of recent abominations, I'd happily rate that at around eleventy-three.

Steve ( @[email protected] ) @g0lfp

15 days ago

@CSG1973 We don't want her!

Steve ( @[email protected] ) @g0lfp

15 days ago

@tanya_tanlb @RupertLowe10 @ChrisVinceMP It should be a packed house, somehow, I doubt there will be very many there. A true reflection of how seriously they take the threat.

Steve ( @[email protected] ) @g0lfp

15 days ago

@MisanthropeGirl You think? I'm torn... Reform should clean up, but it might be because Restore aren't GE ready yet. Who knows?

Steve ( @[email protected] ) @g0lfp

15 days ago · Totland

@JustMyCupOfKaty Do it! :-)

Steve ( @[email protected] ) @g0lfp

18 days ago · Shanklin

@NaomiLWood we were saying....

Alan

@A1an_M

19 days ago

I spent a large part of yesterday trying to explain to people who supposedly are proponents of science what a "confounding variable" is. Rather than say the same thing again today to about 100 people in about 100 different replies, I'm going to write it all in one place, here. When scientists do science, in the form of an experiment or study, they will ultimately write it up in a standard report format containing the same sections: Abstract Introduction Method Results Discussion References One of the most important aspects of the Discussion is a critical analysis of what was done. What went well, what could have been done better, what should be done next time. In particular, the authors attempt to identify if there are any "confounders" which may have influenced the results and rendered them invalid. Let's take the example of a medicine in a clinical trial. We might, if we are ethical scientists, want to study whether a particular medicine causes adverse effects to those taking it before letting it loose in the wild. So we might recruit some people for a trial, and divide them into two groups. The first receives the actual medicine, the second receives a placebo. We might then monitor the recruits for a few months (or, preferably, a much longer period) on a daily basis and note any illnesses suffered in both groups. We would then do a statistical analysis on the results from the two groups. If the results of that analysis showed that there was no statistical difference in the levels and types of illness suffered in the two groups, we might then conclude that no adverse effects were caused by the medicine. If, on the other hand, there was a significant difference between the two groups, that would point towards the need for further study and might lead us to conclude that the medicine was the cause of the difference. The key thing here with our experimental design is that we want to make sure that the two groups in the study - the experimental group who receive the medicine and the control group who do not - are, in every other way, identical. Because if they're not, those differences might have caused the effect we observed, rather than the differences we created in our experiment. What factors might make these two groups different? 1. Age differences. If one group was older, we might expect they might suffer more illness than the younger group. 2. Gender. Dependent on the medicine, males or females might be more affected. If the groups weren't balanced for gender, this might distort the reported illness results. 3. Health differences. If one group had poorer general health than the other at the beginning of the trial, we might expect them to report more illness during the trial. These are all examples of "confounding variables". Factors which we did not control but which might influence the outcome and render our results invalid. So in our experimental design we would want to make sure the experimental group and the control group are closely matched for age, gender and health status. Which brings me onto climate change. Climate scientists contend that Carbon Dioxide created by human activity in the industrial age is causing global atmospheric temperatures to increase. As evidence, they point to an increase in global atmospheric temperatures over the last 200 years or so. So far so good. Temperatures have, broadly, risen during that time. There are plenty of other things to criticise about this hypothesis and about climate "science" in general but that is for another time. Yesterday we saw, all over the media, headlines about new record May temperatures of 35 degrees at Kew and Heathrow, and below the headlines was text saying that experts were saying this was another example of evidence of how the climate is warming. Now I don't deny that it's been hot the last couple of days - where I am it has been around 32 degrees - so I don't doubt that the May record may have been broken somewhere in the country. But the specific problem I have is with the temperatures at Heathrow and Kew, or indeed anywhere close to London or a big urban area being used as the evidence that the May record has been broken,or that they are evidence of atmospheric warming. Why? Because of a confounding variable. When we say a temperature record has been broken, we need to make sure we are comparing apples with apples. So not only do we need to compare temperatures that were measured in the same site using the same type of equipment in both instances - we need to make sure that the sites themselves have not changed. We know that modern urban areas create a "heat island" effect. The expanses of heat-retaining materials like concrete, asphalt and cement retain heat during the day and release it slowly overnight, leading to higher daytime and nighttime temperatures. Added to which are the many buildings and vehicles in urban areas generating their own heat. All of this means that temperatures in, or close to, an urban area are typically several degrees warmer than in countryside some distance away. Given the expansion and urbanisation of London over the last century, this effect will only have grown over time. Arup measured this effect in London and concluded that temperatures there are often 4.5 degrees hotter than in the surrounding countryside (see first comment for link). This effect obviously varies between different parts of London, as shown on the heat map, and reduces as you move away from central London, but even at Kew, the effect is estimated to cause temperatures to be 0.9 degrees higher than would be the case if Kew was sited in the countryside. And Heathrow clearly creates its own heat island effect given the scale of the airport and the big expanses of heat absorbing materials there. So if we are going to use temperatures measured in, or close to, London as evidence of atmospheric warming, we have a problem. We have a significant confounding variable. The warming caused by the heat island effect is going to add to any warming in the atmosphere, and give us an exaggerated result. You can perhaps forgive tabloid newspapers for running headlines about this, just quoting the raw temperatures measured. They want to make money and it being very hot outside is a great news story. And urban areas becoming increasingly hot in summer is an issue in its own right. But what is unforgiveable is people who claim to be scientists using these measurements as evidence of atmospheric warming, when there's such a glaring confounding variable influencing the data. How would a proper scientist deal with this confounder? Well, they might say "from now on, we will only use temperatures from rural weather stations which are not subject to urban heat island effects, and we will only declare records on the basis of those measurements" And they might say "we will not use temperature measurements from areas subject to urban heat island effects as evidence of atmospheric warming". But the Met Office and the climate science people aren't saying that. They're going with the artificially inflated temperatures. Because they have an agenda to push, a vast Net Zero industry to sustain, research grants to chase, and any evidence, however shonky, which backs up the global warming narrative is welcome. This isn't science!