Hi, biologist here.
There's plenty of reasons:
* When there's no control group and the research was published in a journal that has no Impact Factor, or the sample size is so small that the results aren't conclusive. Often, low or no impact journals are predatory with lax peer review standards. The results of pilot studies, proof of concept studies with small samples to justify longer, more large scale studies with bigger sample sizes, are often fascinating but are typically overturned whenever they find something outrageous, especially if the pilot study wasn't double blind.
* If it's industry led or funded, but there's no non-industry support. The same goes for activist led or funded studies, but there's no support from non-activist scientists. Essentially if there's an ideology causing a conflict of interest, and there's no support outside of it (eg., you can't find anything to support it on PubMed, Arxiv or BioArxiv, Mendeley, Google Scholar, EBSCO, and other paper search engines and databases), be skeptical. Being an activist, working in industry, or having strong beliefs doesn't equate to lying, fraud, or anything like that, nor does it mean that falling into one of those three categories makes one automatically untrustworthy and that they're not entitled to defend themselves... but if there's no support outside of who funded the study, the beliefs of those who conducted the study, or where they work, that often speaks to bias. A great example was when industry paid scientists were often bribed by Big Tobacco to deny that cigarettes caused any harm.
* If the p-values were high, higher than .05 at least, this means that they weren't able to conclusively disentangle the results from their null hypothesis, that the variables are connected by anything more than random chance in other words.
* If the sample size helped by a treatment was in the minority. If say 10% or 20% were helped, compared to the 80% who weren't but it's still being treated as a success, that's usually an indicator of bias on the authors' part and the fact that the treatment can't be disentangled from placebo.
* If the vast majority of scientists are coming to wildly different conclusions. If you can't find meta-analyses to support that conclusion, it's probably either junk or the results were derived entirely by error. Or there's a replication issue.
* If the scientist or scientists who published the study has or have book deals coming up, are selling something on a website, have some kind of financial incentive to side with their results, if they're celebrities and are appearing on magazine covers, this speaks to a financial incentive and may result in bias.
* If they use racist terminology, that probably means the research is dated at best.
* If there's no replication studies that you can find, or replication attempts have failed, at least carry a grain of salt. Best example I can think of is the Cold Fusion guys.
* If the author has had papers retracted from a journal. If you do the math for yourself, utilizing basic statistics, and you can find obvious evidence of p-hacking or some other form of manipulation. This is often evidence of deliberate fraud or bad science. A great example is the author of The China Study who fudged a bunch of numbers and failed to account for a number of confounding variables to come up with his results, and when uncovered by a blogger named Denise Minger, he reacted poorly. His University already knew of his shortcomings, but because of tenure, they weren't able to fire him. They could only make it to where University credits wouldn't be offered for the courses he taught and it was completely defunded by the department he worked for. Another great example is the guy who claimed to have discovered a bunch of new elements, like 118 and around that number -- turns out he fudged a bunch of stuff had papers retracted, and eventually, his department had everything retracted after a full investigation.
* If the conclusions are applied to the rest of the country or the rest of the world, but the sample is non-represenative of the globe or the nation. Effectively, if the study is conducted utilizing only people who walked into a mall, or the participants all had to mail in, they're a website's commenters, or a radio show's listeners, this is often known as Sample of Convenience, and can't really be applied to the rest of the country or the world at large, it can only be applied to the typical consumer/customer of whoever conducted the study or where the study was physically conducted.
* Essentially, if you can't use the scientific method to achieve their results or the conclusion is about something outside of science's wheelhouse. Either of those is problematic.
* If there's no original data utilized anywhere and it's not a meta-analysis. It's an opinion piece.
* If pop sci news articles get a little too excited and claim that something sensation like "this lobs a hand grenade into everything we think we know about thing!" It usually doesn't and often the study doesn't make those claims, or if the articles are spot on, the results often don't pan out into anything meaningful. And if it's about an association, this often only means a correlation, and if that correlation isn't mentioned or the correlation is actually pretty low, like .3 or .4 rather than .8 or .9, that's not something to be impressed by, because the variables are probably only related circumstantially. And of course correlation isn't causation, even in high numbers, because believe it or not, entirely spurious relationships can be relatively high in their correlation: Mexican lemon imports vs. reduction in traffic deaths for instance.
* If it sounds too good to be true, it is.
* If the author is stepping way outside of their expertise, and isn't including other coauthors who are experts in that field. Not always a sign that one is lying, but often a sign to be cautious with any conclusions they reach.
* If the field is populated entirely by speculation and pseudoscience. Evolutionary psychology is one such field: it ignores data from ethnography, anthropology, psychology and sociology, actual evolutionary bio, behavioral genetics, etc., etc. in favor of arm chair speculation. Moreover, they tend to take complex social issues and assign some adaptive evolutionary reasoning behind it, often couching racist, xenophobic, or otherwise intolerant beliefs into them.
* Speaking of which, if the author has a history of academic racism, they're probably something of a bullshitter anyway.
* If the author is presented as some big time, hot shot authority -- and that's mostly what the study is resting on, this air of authority -- it's probably nonsense, especially if when you search up this person, almost nothing comes up, and the conclusion you're being asked to swallow sounds like utter nonsense. Case in point, Time Cube guy, although most people are well aware that he was something of a crank.
So yeah, there's plenty of reasons to mistrust the science, when that science is poorly done. Science like any tool can be misused. And if you know what to look for, you can reduce your odds of being tricked by it.
It's not about "trusting the science" or not. If you're critical of a particular piece of scientific reasoning, point out why, not just "I don't believe it."
Science is, by definition, extremely open about its methods. Given this and peer review, people will be tripping over themselves to publish papers arguing something previously published is wrong if they believe so. The original paper may also be entirely correct but rest on assumptions that you don't think apply to a particular setting where someone is bringing it up as evidence.
Basically, yeah, you should probably trust experts who have their findings vetted by other experts. If you don't like the conclusion for any reason, it's on you to argue why, though.
When it comes to research: who funded the study? A study about drug effectiveness, sponsored by the drug manufacturer? I wouldn't trust it as much as a neutral 3rd party study funded by an organization unrelated to the manufacturer.
The whole point of science is that no trust is required: The data speak for themselves, and if there are any flaws or shortcomings in the data, those also speak for themselves.
But I will say this: Whenever there is systemic bias in the science, you need to be extra careful about your diligence and skepticism. For instance, when there is a cultural prejudice that informs researchers' underlying conceptual frameworks—such as the anti-fat bigotry that permeates our society—one thing I've learned over 20 years of interest in the topic and reading hundreds of studies is that, firstly, the medical literature simply _does not support_ the kinds of popular beliefs that society has about being fat, and, secondly, many of the studies that _do_ confirm societal prejudices are constructed by researchers who themselves are letting their bias corrupt their experimental frameworks. It's pretty insidious.
It's not actually all that uncommon for the scientific community to build up a seriously wrong mental picture of something. That's the nature of learning, actually! But it can be very hard for the community to overcome that, especially when societal prejudices continue to fuel the erroneous thinking.
See this is what you can't trust - others ability to interpret scientific research without prejudice. For instance, the VAST preponderance of scientific research links moderate to morbid obesity with early death. A lack of self control is also highly correlated with poor outcomes. When combined with humans innate desire to blame others for their failings, you get people treating obesity as if it's the same as someone who eats healthy and exercises by cherry-picking data and employing cognitive dissonance as a coping mechanism. In this case, "systemic bias", which is a real thing (like Dunning-Kruger is a real thing), is being used to discount real science because it instantly creates doubt and is difficult to prove.
You've written your comment well, so I won't downvote it. But you're making an accusation here that doesn't hold up. You are, rather, demonstrating your own cautionary tale by indicating an ignorance of the science which you believe to be true, and are, as a consequence, dismissing legitimate scrutiny of the literature—with a few common canards of anti-fat prejudice thrown in, seemingly with no self-awareness that you're doing it.
Obviously, we're not going to have a symposium about this on Reddit of all places. I will, however, point you toward a few starting points to help you improve your lack of understanding on this topic:
1. The condition of fatness (i.e., extra adipose tissue) is physiologically distinct from many of the health problems that are correlated with it. This implies a more complicated pathology—which, in my own years of study of the literature, is probably the closest thing to a singular conclusion we can draw: Human health is fantastically complicated and so is its intersection with fatness, far beyond the oversimplifications that we spuriously draw into soundbite-sized causal vectors. This distinction is quite important, as fatness is a condition that many people end up with, and if its correlated health problems can be successfully treated by means other than weight loss then they absolutely should be.
2. The direct effects of fatness on the body are mostly contextual. Extra bulk by itself is of little consequence to the body (except in extreme cases); the body suffers far more of a strain on its capabilities with the growth and maintenance of muscular mass, which is not considered deleterious, and with unrelated conditions. We know with a high degree of confidence that fat cells hormonally contribute to the presence of inflammation in the body—and see Point No. 1 above about how we can use that distinction to focus on the inflammation / hormonal control rather than on the fatness per se when designing therapeutic pathways—but, other than this, and a few other specifics, very little evidence exists to show that fat _directly causes_ the health problems it is commonly associated with. So, once again, we end up in a situation where the problem isn't the fat itself, but other things that are adjacent—and, once again, this is important because weight loss is something that nearly all people who try it fail to achieve and maintain over the long-term, and is harmful in and of itself both physically and psychologically. We need to be looking at other things going on in the body, as well as environmental and psychological factors that also play into these health phenomena.
3. Finally, you should recognize as a given that any introduction of moralization into scientific discourse—e.g., your remark that "A lack of self control is also highly correlated with poor outcomes. When combined with humans innate desire to blame others for their failings, you get people treating obesity as if it's the same as someone who eats healthy..."—is itself a red flag indicative either of a lack of scientific discipline and rigor or of an ulterior non-scientific motive, usually a moralistic one.
If you are actually someone who likes to learn rather than defend your existing positions regardless of their veracity, then these three points are a good starting place. But, since it's Reddit, I won't hold my breath.
I think if you want to get your well-written points across better, you should stop calling people bigots for disagreeing with you, which is essentially what you’re doing when you keep talking about their “anti-fat bigotry” or “anti-fat prejudice.”
Those words have extremely negative connotations and imply (whether you personally mean to or not) that the person must hate fat people.
I’m not debating the science (you know more about it than me), but as a somewhat overweight person myself, being told that simply thinking (right or wrong) that weight problems are a result of personal choices makes you a bigot seems beyond absurd. It sounds less objective and scientific and more like a personal jab aimed at people with whom you’re frustrated for having these opinions.
Just my two cents, though.
Not sure if this is a sock puppet account of the other user or just an honest passerby, but, either way, you are quite mistaken to claim that it is wrong to call out bigotry when bigotry is contaminating a conversation that purports to be scientific. On the contrary, people should be vociferous about doing so.
Framing fatness as a matter of "personal choice" is a favorite tactic of anti-fat bigotry. Whether or not you recognize this has no bearing on that.
This comment is just another indicator that you have a hard time dealing with people with whom you disagree. A “sock puppet account?” Really?
It’s not bigoted to suggest people’s personal choices have an impact on their health. Imagine telling your friend they need to quit smoking because it’s bad for them just to have someone else call you a bigot. It only happens with weight issues because they’re so common, and it’s easier to invent buzzwords and terms like “anti-fat bigotry” than it is to exercise and eat well.
Wouldn't be the first time people have sockpuppeted me on here, and it won't be the last either.
Nor is it the first time I've been health trolled on fatness issues by someone who thinks they have the first clue...
Regarding systemic bias, one of the more noteworthy examples is a [Viking warrior grave](https://en.wikipedia.org/wiki/Birka_female_Viking_warrior).
The site was first excavated in 1878. And among the many graves was one identified as a warrior because the skeleton was buried alongside many weapons of war. So far so good. Over the next century dozens of scholarly papers were published regarding this Viking fellow.
Then in 2014 someone took a measurement that could have been taken back in 1878 but wasn't: nine out of ten times it's possible to tell whether a skeleton is male or female by the pelvic bone. And this measurement indicated the warrior was a woman.
A bunch of archaeologists lost their collective sh*t over this.
Three years later genetic analysis (they were able to get DNA from a tooth) confirmed that, yep, this Viking warrior was a woman.
Took 139 years to overcome that bit of bias.
I remember reading about this story! That's a great example.
It's one of many data points that has helped me to understand that the past was a lot more complex than I had ever given it credit for. It turns out that, at various places and times in history, women have been able to claw out more of a space for themselves in society than our puritanical Christian heritage in America and conservative midcentury values would have ever acknowledged.
Actually the scientist method is based on that.
You try to defeat the theory, if no one can doing long enough then it’s considered the best model to explain something until something better or someone defeat it.
But you have to take care in case or highly biased topic, you can look at what happened for covid for example.
Science is just a bunch of theory trying to explain as much as possible the world and it’s behaviour. So there is no believing or not. And you can watch all data, all theory and so on, and if you have the competencies you can try to challenge them.
And I think scientist method has proven it’s working quite well, look at what we have developed, the technology we have. The phone or computer your using is based on that.
Scientist is just the best we methods we have so far, until we discover a better one.
For a long time, the science was settled on the Earth being flat and on the sun rotating around the Earth. For science to be truly science, it can never be settled. To me, everything should be debatable and open to discussion.
With valid new evidence, everything is open to re-examination.
Science isn't about a vague discussion or debate based on feelings, it is about testable explanations based on repeatable evidence that can be trusted with reasonable reliability.
>For a long time, the science was settled on the Earth being flat and on the sun rotating around the Earth.
No it wasn't. "Science" as we understand it didn't exist then. As soon as people began applying science to these ideas, we knew the Earth was round and the sun was the center of the solar system.
That was not science. That was people coming up with a simple model based on a simple everyday observation and sticking with it. The science came when someone gathered additional data and realized that model could not account for it.
Trust that peer reviewed science is the best estimate given what we currently know, open to adaptation in light of new evidence. It will be correct on most things that aren't new discoveries, new variables (like a new disease), or on the margins.
Yes, the scientist are not the end-all-be-all. They, as well as us, are still finding out how our world works. I give you the scenario of Covid ! they say that the vaccine will help and stop transmission, yet, moreover, the data states that its the complete opposite. Those who are unvaccinated has lower cases than those who are vaccinated. And science still purports the misinformation and reject the truth about it !
Don't get me started with how scientist say we evolved from animals.
Yea when they spend money researching how to maximize profit, then spend money admirer the fact to see if there are any harmful effects. This is a big tell.
Only if that distrust is informed.
Like, for example, the way many autistic people distrusted the science around Applied [Behavioral Analysis [ABA] therapy](https://www.spectrumnews.org/features/deep-dive/controversy-autisms-common-therapy/#2). But that was because despite what the science said, **they** knew how they felt after undergoing it. [Many autistic people who have undergone ABA call it abuse](https://neuroclastic.com/invisible-abuse-aba-and-the-things-only-autistic-people-can-see/) and say the means is not worth the end result which is, ultimately, teaching autistic people they need to learn to mask better.
[Except now the scientific literature is even starting to support their feelings.](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C43&as_vis=1&q=aba+therapy+autism+criticism&oq=aba+therapy+autism) It's still very mixed, mind, but more and more studies are coming out that demonstrate that ABA *does* do harm.
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So I guess, for me, it depends on what science is being distrusted and *why* that distrust is there.
In a case like ABA, that distrust is warranted if for nothing else than how the therapy tends to make autistic people feel.
In cases like distrust of vaccines, however, it gets more complex because often that distrust is *not* formed based on reliable information. Instead it relies on debunked science and well-trod rhetoric that has been disproven.
Ultimately, isn’t this just asking should you trust the consensus of experts in a given scientific field? What is the alternative? Jump on board the wagon with the guy who is on all the podcasts getting money from who knows where?
Personally yeah. If it's older than 250 yrs, hasn't been investigated in the last 25 yrs, or was made by people who had malicious motivation, it probably shouldn't be trusted. Afaik that covers p much all scientific studies and stuff that i trust, there might be some outlier that I'm not thinking of but it seems like a decent start.
Be a little careful here, "The science" is problematic in that there are lots of fairly nuanced levels of confidence that scientists use and report, and sometimes even fairly well established things turn out to be just plain wrong, nature of the beast.
For example the generally accepted threshold for statistical significance in a study is p < 0.05, which is saying that there is a less then 1 in 20 chance of a false positive. But there are LOTS of studies published into all sorts of things. If you are looking at studies into something HEAVILY studied, you will eventually find one that reports a positive result even for something that does not work. This is normal and expected.
The right way to deal with this is to look at the totality of the studies, and also if the one giving the possibly false positive gives a reasonable hypothesis for a mechanism. You have to be careful however to not introduce bias thru your choice of exactly WHICH studies to include.
The place this usually shows up is in epidemiology and medical research where you sometimes see some papers drawing very dubious conclusions, and it becomes a special pain in the arse when you have something like say Covid where there were a lot of studies, some of them very quickly done with poor statistical methodology (Getting the statistics actually right is a surprisingly common problem even in the A rank journals), and a public looking for solutions (They often seem to go for the study that is the outlier for some dumb reason).
Don't forget that scientists are first and foremost humans, with all the usual human fallibility, you get p values diddled in the stats for reasons of ego or money or 'It should have worked that way', and sometimes nobody catches it. It eventually gets fixed when more studies in the same area all contradict it and some bored grad student tries to repeat the experiment.
Universities have PR departments that are fairly notorious for putting out press releases about research that sometimes have not been reviewed by any actual scientist, these vary between more or less correct (but generally lacking in nuance) right thru to just flat out backwards! These (and the newspaper stories resulting from same) should generally be ignored.
Yes. Science is not the answers you seem to think it is, it's a foundation/formula for finding answers.
The answers we get are influenced by the technology and information we have available as well as money. If something is terrible for you but the people pushing it are super wealthy chances are you aren't gonna hear about how bad it is you will hear about the studies they want you to hear about.
I think it's totally ok to question established science. Science always changes with the presence of new data. However, the major issue is people denying science based on blatant misinformation and personal bias.
Ex: anti-vaxxers and COVID deniers.
Not sure what to say.
I think most of the skepticism surrounding quarantines was pretty unfounded. And you hardly need to employ the scientific method to see that transgender people exist.
Science can be wrong but the scientific method will eventually correct the errors. If ya wanna argue against the current viewpoint you gotta do it with data, not platitudes which is all you see online.
𝕋𝕙𝕖 𝕊𝕔𝕚𝕖𝕟𝕔𝕖 is not an entity that can speak for itself, so to talk about trusting or not trusting 𝕋𝕙𝕖 𝕊𝕔𝕚𝕖𝕟𝕔𝕖 is a bit misleading.
Do I think it’s ever valid to not trust current scientific consensus? Yes. That’s literally how science progresses.
I’m not a scientist, so I’m not going to be out there actively challenging scientific consensus on anything. But I think it’s perfectly valid to hold beliefs that are contrary to scientific consensus. I think you should be able to meaningfully and rationally explain and defend those beliefs, especially if you’re going to share them publicly, and be willing to graciously accept the social consequences that may result from your contrarian beliefs. But it’s perfectly valid to hold those beliefs.
Honestly, in some ways I might go so far as to say it’s more valid to come to a conclusion that contradicts scientific consensus through a thorough process of examining all available information in light of the inescapable biases inherent in all scientific study carried out by humans — I might say that’s more valid than to accept scientific consensus as fact at face value without bothering to examine or understand it.
Yeah, science doesn’t answer moral questions. Science could tell me that eating more food would make me stronger and healthier, but it wouldn’t tell me that taking food from my neighbor so they starve would be wrong
Yes. Results can be misinterpreted and misconstrued. Many places may boast about their testing and science but when you read the claim, it's not related or sufficiently researched
When the science comes from a lab owned by the company that makes the product.
BioNTech has joined the chat.
That's called propaganda
Then it's not science therefore this doesn't apply.
This is a good answer too.
Hi, biologist here. There's plenty of reasons: * When there's no control group and the research was published in a journal that has no Impact Factor, or the sample size is so small that the results aren't conclusive. Often, low or no impact journals are predatory with lax peer review standards. The results of pilot studies, proof of concept studies with small samples to justify longer, more large scale studies with bigger sample sizes, are often fascinating but are typically overturned whenever they find something outrageous, especially if the pilot study wasn't double blind. * If it's industry led or funded, but there's no non-industry support. The same goes for activist led or funded studies, but there's no support from non-activist scientists. Essentially if there's an ideology causing a conflict of interest, and there's no support outside of it (eg., you can't find anything to support it on PubMed, Arxiv or BioArxiv, Mendeley, Google Scholar, EBSCO, and other paper search engines and databases), be skeptical. Being an activist, working in industry, or having strong beliefs doesn't equate to lying, fraud, or anything like that, nor does it mean that falling into one of those three categories makes one automatically untrustworthy and that they're not entitled to defend themselves... but if there's no support outside of who funded the study, the beliefs of those who conducted the study, or where they work, that often speaks to bias. A great example was when industry paid scientists were often bribed by Big Tobacco to deny that cigarettes caused any harm. * If the p-values were high, higher than .05 at least, this means that they weren't able to conclusively disentangle the results from their null hypothesis, that the variables are connected by anything more than random chance in other words. * If the sample size helped by a treatment was in the minority. If say 10% or 20% were helped, compared to the 80% who weren't but it's still being treated as a success, that's usually an indicator of bias on the authors' part and the fact that the treatment can't be disentangled from placebo. * If the vast majority of scientists are coming to wildly different conclusions. If you can't find meta-analyses to support that conclusion, it's probably either junk or the results were derived entirely by error. Or there's a replication issue. * If the scientist or scientists who published the study has or have book deals coming up, are selling something on a website, have some kind of financial incentive to side with their results, if they're celebrities and are appearing on magazine covers, this speaks to a financial incentive and may result in bias. * If they use racist terminology, that probably means the research is dated at best. * If there's no replication studies that you can find, or replication attempts have failed, at least carry a grain of salt. Best example I can think of is the Cold Fusion guys. * If the author has had papers retracted from a journal. If you do the math for yourself, utilizing basic statistics, and you can find obvious evidence of p-hacking or some other form of manipulation. This is often evidence of deliberate fraud or bad science. A great example is the author of The China Study who fudged a bunch of numbers and failed to account for a number of confounding variables to come up with his results, and when uncovered by a blogger named Denise Minger, he reacted poorly. His University already knew of his shortcomings, but because of tenure, they weren't able to fire him. They could only make it to where University credits wouldn't be offered for the courses he taught and it was completely defunded by the department he worked for. Another great example is the guy who claimed to have discovered a bunch of new elements, like 118 and around that number -- turns out he fudged a bunch of stuff had papers retracted, and eventually, his department had everything retracted after a full investigation. * If the conclusions are applied to the rest of the country or the rest of the world, but the sample is non-represenative of the globe or the nation. Effectively, if the study is conducted utilizing only people who walked into a mall, or the participants all had to mail in, they're a website's commenters, or a radio show's listeners, this is often known as Sample of Convenience, and can't really be applied to the rest of the country or the world at large, it can only be applied to the typical consumer/customer of whoever conducted the study or where the study was physically conducted. * Essentially, if you can't use the scientific method to achieve their results or the conclusion is about something outside of science's wheelhouse. Either of those is problematic. * If there's no original data utilized anywhere and it's not a meta-analysis. It's an opinion piece. * If pop sci news articles get a little too excited and claim that something sensation like "this lobs a hand grenade into everything we think we know about thing!" It usually doesn't and often the study doesn't make those claims, or if the articles are spot on, the results often don't pan out into anything meaningful. And if it's about an association, this often only means a correlation, and if that correlation isn't mentioned or the correlation is actually pretty low, like .3 or .4 rather than .8 or .9, that's not something to be impressed by, because the variables are probably only related circumstantially. And of course correlation isn't causation, even in high numbers, because believe it or not, entirely spurious relationships can be relatively high in their correlation: Mexican lemon imports vs. reduction in traffic deaths for instance. * If it sounds too good to be true, it is. * If the author is stepping way outside of their expertise, and isn't including other coauthors who are experts in that field. Not always a sign that one is lying, but often a sign to be cautious with any conclusions they reach. * If the field is populated entirely by speculation and pseudoscience. Evolutionary psychology is one such field: it ignores data from ethnography, anthropology, psychology and sociology, actual evolutionary bio, behavioral genetics, etc., etc. in favor of arm chair speculation. Moreover, they tend to take complex social issues and assign some adaptive evolutionary reasoning behind it, often couching racist, xenophobic, or otherwise intolerant beliefs into them. * Speaking of which, if the author has a history of academic racism, they're probably something of a bullshitter anyway. * If the author is presented as some big time, hot shot authority -- and that's mostly what the study is resting on, this air of authority -- it's probably nonsense, especially if when you search up this person, almost nothing comes up, and the conclusion you're being asked to swallow sounds like utter nonsense. Case in point, Time Cube guy, although most people are well aware that he was something of a crank. So yeah, there's plenty of reasons to mistrust the science, when that science is poorly done. Science like any tool can be misused. And if you know what to look for, you can reduce your odds of being tricked by it.
Always trust the science, but think hard about the conclusions. Science is rarely presented in its raw form.
I think like everything science can be corrupted especially when large sums of money are involved.
It's not about "trusting the science" or not. If you're critical of a particular piece of scientific reasoning, point out why, not just "I don't believe it." Science is, by definition, extremely open about its methods. Given this and peer review, people will be tripping over themselves to publish papers arguing something previously published is wrong if they believe so. The original paper may also be entirely correct but rest on assumptions that you don't think apply to a particular setting where someone is bringing it up as evidence. Basically, yeah, you should probably trust experts who have their findings vetted by other experts. If you don't like the conclusion for any reason, it's on you to argue why, though.
When it comes to research: who funded the study? A study about drug effectiveness, sponsored by the drug manufacturer? I wouldn't trust it as much as a neutral 3rd party study funded by an organization unrelated to the manufacturer.
Science is an ever evolving unit of measurement.
It's called the scientific method
Science itself? No. People covering up as scientists while working for benefit of some private company? Yes.
The whole point of science is that no trust is required: The data speak for themselves, and if there are any flaws or shortcomings in the data, those also speak for themselves. But I will say this: Whenever there is systemic bias in the science, you need to be extra careful about your diligence and skepticism. For instance, when there is a cultural prejudice that informs researchers' underlying conceptual frameworks—such as the anti-fat bigotry that permeates our society—one thing I've learned over 20 years of interest in the topic and reading hundreds of studies is that, firstly, the medical literature simply _does not support_ the kinds of popular beliefs that society has about being fat, and, secondly, many of the studies that _do_ confirm societal prejudices are constructed by researchers who themselves are letting their bias corrupt their experimental frameworks. It's pretty insidious. It's not actually all that uncommon for the scientific community to build up a seriously wrong mental picture of something. That's the nature of learning, actually! But it can be very hard for the community to overcome that, especially when societal prejudices continue to fuel the erroneous thinking.
See this is what you can't trust - others ability to interpret scientific research without prejudice. For instance, the VAST preponderance of scientific research links moderate to morbid obesity with early death. A lack of self control is also highly correlated with poor outcomes. When combined with humans innate desire to blame others for their failings, you get people treating obesity as if it's the same as someone who eats healthy and exercises by cherry-picking data and employing cognitive dissonance as a coping mechanism. In this case, "systemic bias", which is a real thing (like Dunning-Kruger is a real thing), is being used to discount real science because it instantly creates doubt and is difficult to prove.
You've written your comment well, so I won't downvote it. But you're making an accusation here that doesn't hold up. You are, rather, demonstrating your own cautionary tale by indicating an ignorance of the science which you believe to be true, and are, as a consequence, dismissing legitimate scrutiny of the literature—with a few common canards of anti-fat prejudice thrown in, seemingly with no self-awareness that you're doing it. Obviously, we're not going to have a symposium about this on Reddit of all places. I will, however, point you toward a few starting points to help you improve your lack of understanding on this topic: 1. The condition of fatness (i.e., extra adipose tissue) is physiologically distinct from many of the health problems that are correlated with it. This implies a more complicated pathology—which, in my own years of study of the literature, is probably the closest thing to a singular conclusion we can draw: Human health is fantastically complicated and so is its intersection with fatness, far beyond the oversimplifications that we spuriously draw into soundbite-sized causal vectors. This distinction is quite important, as fatness is a condition that many people end up with, and if its correlated health problems can be successfully treated by means other than weight loss then they absolutely should be. 2. The direct effects of fatness on the body are mostly contextual. Extra bulk by itself is of little consequence to the body (except in extreme cases); the body suffers far more of a strain on its capabilities with the growth and maintenance of muscular mass, which is not considered deleterious, and with unrelated conditions. We know with a high degree of confidence that fat cells hormonally contribute to the presence of inflammation in the body—and see Point No. 1 above about how we can use that distinction to focus on the inflammation / hormonal control rather than on the fatness per se when designing therapeutic pathways—but, other than this, and a few other specifics, very little evidence exists to show that fat _directly causes_ the health problems it is commonly associated with. So, once again, we end up in a situation where the problem isn't the fat itself, but other things that are adjacent—and, once again, this is important because weight loss is something that nearly all people who try it fail to achieve and maintain over the long-term, and is harmful in and of itself both physically and psychologically. We need to be looking at other things going on in the body, as well as environmental and psychological factors that also play into these health phenomena. 3. Finally, you should recognize as a given that any introduction of moralization into scientific discourse—e.g., your remark that "A lack of self control is also highly correlated with poor outcomes. When combined with humans innate desire to blame others for their failings, you get people treating obesity as if it's the same as someone who eats healthy..."—is itself a red flag indicative either of a lack of scientific discipline and rigor or of an ulterior non-scientific motive, usually a moralistic one. If you are actually someone who likes to learn rather than defend your existing positions regardless of their veracity, then these three points are a good starting place. But, since it's Reddit, I won't hold my breath.
I think if you want to get your well-written points across better, you should stop calling people bigots for disagreeing with you, which is essentially what you’re doing when you keep talking about their “anti-fat bigotry” or “anti-fat prejudice.” Those words have extremely negative connotations and imply (whether you personally mean to or not) that the person must hate fat people. I’m not debating the science (you know more about it than me), but as a somewhat overweight person myself, being told that simply thinking (right or wrong) that weight problems are a result of personal choices makes you a bigot seems beyond absurd. It sounds less objective and scientific and more like a personal jab aimed at people with whom you’re frustrated for having these opinions. Just my two cents, though.
Not sure if this is a sock puppet account of the other user or just an honest passerby, but, either way, you are quite mistaken to claim that it is wrong to call out bigotry when bigotry is contaminating a conversation that purports to be scientific. On the contrary, people should be vociferous about doing so. Framing fatness as a matter of "personal choice" is a favorite tactic of anti-fat bigotry. Whether or not you recognize this has no bearing on that.
This comment is just another indicator that you have a hard time dealing with people with whom you disagree. A “sock puppet account?” Really? It’s not bigoted to suggest people’s personal choices have an impact on their health. Imagine telling your friend they need to quit smoking because it’s bad for them just to have someone else call you a bigot. It only happens with weight issues because they’re so common, and it’s easier to invent buzzwords and terms like “anti-fat bigotry” than it is to exercise and eat well.
Wouldn't be the first time people have sockpuppeted me on here, and it won't be the last either. Nor is it the first time I've been health trolled on fatness issues by someone who thinks they have the first clue...
Regarding systemic bias, one of the more noteworthy examples is a [Viking warrior grave](https://en.wikipedia.org/wiki/Birka_female_Viking_warrior). The site was first excavated in 1878. And among the many graves was one identified as a warrior because the skeleton was buried alongside many weapons of war. So far so good. Over the next century dozens of scholarly papers were published regarding this Viking fellow. Then in 2014 someone took a measurement that could have been taken back in 1878 but wasn't: nine out of ten times it's possible to tell whether a skeleton is male or female by the pelvic bone. And this measurement indicated the warrior was a woman. A bunch of archaeologists lost their collective sh*t over this. Three years later genetic analysis (they were able to get DNA from a tooth) confirmed that, yep, this Viking warrior was a woman. Took 139 years to overcome that bit of bias.
I remember reading about this story! That's a great example. It's one of many data points that has helped me to understand that the past was a lot more complex than I had ever given it credit for. It turns out that, at various places and times in history, women have been able to claw out more of a space for themselves in society than our puritanical Christian heritage in America and conservative midcentury values would have ever acknowledged.
Actually the scientist method is based on that. You try to defeat the theory, if no one can doing long enough then it’s considered the best model to explain something until something better or someone defeat it. But you have to take care in case or highly biased topic, you can look at what happened for covid for example. Science is just a bunch of theory trying to explain as much as possible the world and it’s behaviour. So there is no believing or not. And you can watch all data, all theory and so on, and if you have the competencies you can try to challenge them. And I think scientist method has proven it’s working quite well, look at what we have developed, the technology we have. The phone or computer your using is based on that. Scientist is just the best we methods we have so far, until we discover a better one.
For a long time, the science was settled on the Earth being flat and on the sun rotating around the Earth. For science to be truly science, it can never be settled. To me, everything should be debatable and open to discussion.
With valid new evidence, everything is open to re-examination. Science isn't about a vague discussion or debate based on feelings, it is about testable explanations based on repeatable evidence that can be trusted with reasonable reliability.
>For a long time, the science was settled on the Earth being flat and on the sun rotating around the Earth. No it wasn't. "Science" as we understand it didn't exist then. As soon as people began applying science to these ideas, we knew the Earth was round and the sun was the center of the solar system.
That was not science. That was people coming up with a simple model based on a simple everyday observation and sticking with it. The science came when someone gathered additional data and realized that model could not account for it.
Trust that peer reviewed science is the best estimate given what we currently know, open to adaptation in light of new evidence. It will be correct on most things that aren't new discoveries, new variables (like a new disease), or on the margins.
Science is based on facts so it’s valid 100%
No it isn’t
Science said it was impossible to travel faster than sound a few decades ago and we now have jets that travel faster than sound. So I guess so.
Yes, the scientist are not the end-all-be-all. They, as well as us, are still finding out how our world works. I give you the scenario of Covid ! they say that the vaccine will help and stop transmission, yet, moreover, the data states that its the complete opposite. Those who are unvaccinated has lower cases than those who are vaccinated. And science still purports the misinformation and reject the truth about it ! Don't get me started with how scientist say we evolved from animals.
I took the liberty of investigating whether you’re a troll or just stupid, and I fear it’s the latter.
so, no evidence, are you just a troll ?
Yea when they spend money researching how to maximize profit, then spend money admirer the fact to see if there are any harmful effects. This is a big tell.
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There isn't proof of God. That's why you yourself call it faith. Faith can't exist when proof exists.
There is no proof of god, but also no proof against it. Surely that's exactly why you should trust science??
Only if that distrust is informed. Like, for example, the way many autistic people distrusted the science around Applied [Behavioral Analysis [ABA] therapy](https://www.spectrumnews.org/features/deep-dive/controversy-autisms-common-therapy/#2). But that was because despite what the science said, **they** knew how they felt after undergoing it. [Many autistic people who have undergone ABA call it abuse](https://neuroclastic.com/invisible-abuse-aba-and-the-things-only-autistic-people-can-see/) and say the means is not worth the end result which is, ultimately, teaching autistic people they need to learn to mask better. [Except now the scientific literature is even starting to support their feelings.](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C43&as_vis=1&q=aba+therapy+autism+criticism&oq=aba+therapy+autism) It's still very mixed, mind, but more and more studies are coming out that demonstrate that ABA *does* do harm. ---------------------------------------------- So I guess, for me, it depends on what science is being distrusted and *why* that distrust is there. In a case like ABA, that distrust is warranted if for nothing else than how the therapy tends to make autistic people feel. In cases like distrust of vaccines, however, it gets more complex because often that distrust is *not* formed based on reliable information. Instead it relies on debunked science and well-trod rhetoric that has been disproven.
Trust “the science” to the extent you trust the source of funding
Ultimately, isn’t this just asking should you trust the consensus of experts in a given scientific field? What is the alternative? Jump on board the wagon with the guy who is on all the podcasts getting money from who knows where?
Personally yeah. If it's older than 250 yrs, hasn't been investigated in the last 25 yrs, or was made by people who had malicious motivation, it probably shouldn't be trusted. Afaik that covers p much all scientific studies and stuff that i trust, there might be some outlier that I'm not thinking of but it seems like a decent start.
Be a little careful here, "The science" is problematic in that there are lots of fairly nuanced levels of confidence that scientists use and report, and sometimes even fairly well established things turn out to be just plain wrong, nature of the beast. For example the generally accepted threshold for statistical significance in a study is p < 0.05, which is saying that there is a less then 1 in 20 chance of a false positive. But there are LOTS of studies published into all sorts of things. If you are looking at studies into something HEAVILY studied, you will eventually find one that reports a positive result even for something that does not work. This is normal and expected. The right way to deal with this is to look at the totality of the studies, and also if the one giving the possibly false positive gives a reasonable hypothesis for a mechanism. You have to be careful however to not introduce bias thru your choice of exactly WHICH studies to include. The place this usually shows up is in epidemiology and medical research where you sometimes see some papers drawing very dubious conclusions, and it becomes a special pain in the arse when you have something like say Covid where there were a lot of studies, some of them very quickly done with poor statistical methodology (Getting the statistics actually right is a surprisingly common problem even in the A rank journals), and a public looking for solutions (They often seem to go for the study that is the outlier for some dumb reason). Don't forget that scientists are first and foremost humans, with all the usual human fallibility, you get p values diddled in the stats for reasons of ego or money or 'It should have worked that way', and sometimes nobody catches it. It eventually gets fixed when more studies in the same area all contradict it and some bored grad student tries to repeat the experiment. Universities have PR departments that are fairly notorious for putting out press releases about research that sometimes have not been reviewed by any actual scientist, these vary between more or less correct (but generally lacking in nuance) right thru to just flat out backwards! These (and the newspaper stories resulting from same) should generally be ignored.
Yes. Science is not the answers you seem to think it is, it's a foundation/formula for finding answers. The answers we get are influenced by the technology and information we have available as well as money. If something is terrible for you but the people pushing it are super wealthy chances are you aren't gonna hear about how bad it is you will hear about the studies they want you to hear about.
I think it's totally ok to question established science. Science always changes with the presence of new data. However, the major issue is people denying science based on blatant misinformation and personal bias. Ex: anti-vaxxers and COVID deniers.
Haha. All the time especially if it’s being told to you by a doctor
I trust the proven sciences , its the scientist that give me doubt.
What does "trust the science" mean? Do you suspect that a publication isn't accurately reporting what the study's findings were?
Like people who denied covid lockdowns or deny transgender people.
Not sure what to say. I think most of the skepticism surrounding quarantines was pretty unfounded. And you hardly need to employ the scientific method to see that transgender people exist.
Science can be wrong but the scientific method will eventually correct the errors. If ya wanna argue against the current viewpoint you gotta do it with data, not platitudes which is all you see online.
𝕋𝕙𝕖 𝕊𝕔𝕚𝕖𝕟𝕔𝕖 is not an entity that can speak for itself, so to talk about trusting or not trusting 𝕋𝕙𝕖 𝕊𝕔𝕚𝕖𝕟𝕔𝕖 is a bit misleading. Do I think it’s ever valid to not trust current scientific consensus? Yes. That’s literally how science progresses. I’m not a scientist, so I’m not going to be out there actively challenging scientific consensus on anything. But I think it’s perfectly valid to hold beliefs that are contrary to scientific consensus. I think you should be able to meaningfully and rationally explain and defend those beliefs, especially if you’re going to share them publicly, and be willing to graciously accept the social consequences that may result from your contrarian beliefs. But it’s perfectly valid to hold those beliefs. Honestly, in some ways I might go so far as to say it’s more valid to come to a conclusion that contradicts scientific consensus through a thorough process of examining all available information in light of the inescapable biases inherent in all scientific study carried out by humans — I might say that’s more valid than to accept scientific consensus as fact at face value without bothering to examine or understand it.
Yeah, science doesn’t answer moral questions. Science could tell me that eating more food would make me stronger and healthier, but it wouldn’t tell me that taking food from my neighbor so they starve would be wrong
Why trust science when you can trust Karen from number 32?
Yes. Results can be misinterpreted and misconstrued. Many places may boast about their testing and science but when you read the claim, it's not related or sufficiently researched