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Most Scientists 'Can't Replicate Studies By Their Peers' (bbc.com)
Science is facing a "reproducibility crisis" where more than two-thirds of researchers have tried and failed to reproduce another scientist's experiments, research suggests. From a report: This is frustrating clinicians and drug developers who want solid foundations of pre-clinical research to build upon. From his lab at the University of Virginia's Centre for Open Science, immunologist Dr Tim Errington runs The Reproducibility Project, which attempted to repeat the findings reported in five landmark cancer studies. "The idea here is to take a bunch of experiments and to try and do the exact same thing to see if we can get the same results." You could be forgiven for thinking that should be easy. Experiments are supposed to be replicable. The authors should have done it themselves before publication, and all you have to do is read the methods section in the paper and follow the instructions. Sadly nothing, it seems, could be further from the truth.
If you can't reproduce it, it's either fake or you were just being sloppy. Either way, it's no wonder ordinary civilians have doubts.
In the experimental protocols listed in a paper, it is not unusual to have a method's section that is more or less an executive summary rather than a very detailed account of the underlying protocol. This is for two reasons: to great a level of detail leads to a methods section as big as the publication that the paper appears in, and second because many protocols more or less boil down to using a particular series kit or out-sourced lab service. Most journals require data supplements where an author must share their datasets in electronic form as an online addendum to the publication. I would support a similar requirement for a long-form protocol for reproduction of the study.
That said, some protocols necessarily take a lot of money, special equipment, a carefully selected population of volunteers, and time. Reproducing some studies can be outright impractical.
In computational biology and other computational extensions of the physical science, the reproducibility basically comes in the form of requirements to provide the software and raw data for a study. It's easy for the individual that compiles this information to verify that they get the same result as the one they report in the article. The concern there boils down to the provenance of the source data, which may be from registries, public data sets, or some combination of public and private data.
Many studies have been done on anthropic climate change, but almost no experiments.
Scientists are not rewarded for reproducing/debunking previous work. You can't easily get it published, because it is not regarded as new. Honestly, I think grad student projects should be almost entirely reproducing other results. It would insure that every important result is reproduced, and increase the emphasis of doing the science correctly rather than finding some novel result (which is usually a 2 sigma result which again can't be reproduced).
This is medical research, not science. Medicine uses science because often the best way to cure something is to understand it but, very importantly, it has a very different motivation to science. Finding a "magic" pill which cures disease X without side effects but whose mechanism is completely unknown is great medicine but appalling science. Science is all about understanding how things work, medicine is all about treating human ailments.
This leads to a different approach using the tools of science. Medical researchers tend to focus far more on correlation over causation because that is what is most important to this. Unfortunately this approach leaves them open to random statistical effects which require a very good understanding of statistics to avoid and even then it can still be very easy to fool yourself e.g. the Monty Hall effect.
So lets call this problem what it is: a problem with medical research.
The human body is the most complex organism in the known universe so there's nothing to be sneezed at or be surprised by. For instance recent studies have shown that for a lot of people placebo works even when people have a perfect knowledge that they are given placebo.
As another confirmation, the brain has the ability to directly change/affect the chemical processes in the body as demonstrated by Wim Hof who can manage his body's temperature at will.
Many studies have been done on anthropic climate change, but almost no experiments.
The infrared absorption of carbon dioxide is experimentally measured in the laboratory. And there is a vast amount of measured data on the earth's atmosphere and climate, from surface, atmospheric, and orbital probes, not to mention probes of other planets; and we acquire terabytes of additional data every year.
The basics of Earth's energy balance are well understood, and they are understood, in part, because of this vast amount of experimental and observational data.
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It's not heresy if the science is sound. Simply questioning isn't valid, though.
Questioning, of course, is always valid. But "questioning" is useless when the questioner has no interest in listening to anybody answering the question.
Far too much of the "questioning" about climate science is from people who have no interest in any of the science, the measurements, or the data, and won't bother to learn anything about it.
http://www.geoffreylandis.com
he infrared absorption of carbon dioxide is experimentally measured in the laboratory
No one rational doubts this. That has never been what the climate change debate was about. But the atmosphere is not a bottle of air, or even a bottle of air and water (any modern meteorological model treats modeling he ocean at least as importantly as modeling the air). The atmosphere+hydrosphere is a complex, evolving system with many feedback mechanisms, both positive and negative.
I mean, really, do you think a climate model is simply modeling a static stack of air with some CO2 in it? Really?
The question is: quantitatively, what rate of human CO2 emission with create what effects, in detail. This is not the sort of science that lends itself to reproducible experiments, but that's fine, neither does astronomy or cosmology. It is, like any science, required to make falsifiable quantitative predictions.
And, frankly, the best models aren't doing so well, giving about 2 sigmas of accuracy. If you generated hundreds of models at random, you'd expect a couple dozen to have 2 sigmas of accuracy. That doesn't mean the models are flawed in any fundamental way, but there's a big gap between "not fundamentally flawed" and "great, proven science".
Socialism: a lie told by totalitarians and believed by fools.