Who does not know the historical phrase “…One small step for (a) man; one giant leap for mankind?”
It is too early to say (and we are too used to the bad news of a decaying society), but the fact that a series of articles on epidemiological junk science have appeared recently on major press may give some (extremely conservative!) hope that “public health” is finally losing credibility.
Not only have we seen the important piece on the NY Times we are discussing in a multi-part commentary, but we also see “Scientists do the numbers”, “Flip-flopping on issues doesn’t just happen in politics”, “The rush to publish: a problem?”, and “Which studies you should believe”, all from the Los Angeles Times.
Are the obvious contradictions of the junk science industry coming to the surface, or is this just a glitch in the fraud-making machine? Too early to tell.
Or course, in this volley of denunciations, the belief that there is a scientifically established causality for the "smoking causes lung cancer" issue MUST be preserved. Thus, even the “scientists do the numbers” piece must contain the reassuring statement: “Stampfer cites examples of findings of epidemiology that, he says, have stood the test of time: smoking’s link to lung cancer, to name the most notable.”
However, the only reasons why the link has “withstood the test of time” are: a) clinical trials are virtually impossible; b) the scientific opposition or criticism to the belief has been silenced for good with slander and intimidation.
Putting aside the passive smoking “studies” which are an obvious fraud, a reality stands: even the studies on active smoking are affected by the same flaws and shortcomings these articles speak of – with one difference: an immense propaganda machine whose main direct or indirect financer is the pharmaceutical industry has been set in motion to create the mass belief that “smoking kills”. The mass-propaganda aims to substitute the “no one can prove” with the “everybody knows that”.
In the piece “Which studies you should believe” there are some parameters needed to “believe” a study: size of the effect, statistical significance, size of the study and so on, but one – and the most important one – is left out: does the study know what it has measured?
And how can you measure the effects of smoking on diseases that have hundreds of concomitant factors, present in different amounts and interacting in different ways for every individual, all immersed in an ever-changing environment?
Go figure – they didn’t.