Post No.: 0891
Furrywisepuppy says:
It’s vital to read beyond the headlines and understand the details (ideally of the original academic papers or references) when reading science news e.g. when gathering calorie consumption versus BMI data, some people who have low and medium BMI levels may consume enormous amounts of calories but that’s simply because they’re athletes in training; and a lot of overweight and obese people may only be consuming moderate amounts of calories but that’s simply because they’re currently on diets and are trying to lose weight.
But large sections of the media might oversimplify the finding, to the point of being misleading, and claim that ‘obese people don’t eat very much’ in the headlines because they over-generalise ‘one’s BMI’ with ‘one’s fitness’ and/or simply want to create shocking headlines that’ll grab attention and generate social media buzz. The top priority for for-profit media outlets isn’t to educate or be impartial but to generate advertising revenue and/or sell subscriptions i.e. make money. Clickbait headlines are often intentionally very ambiguously worded or plain misleading.
BMI is such a crude measure of health because fit and muscular people can have high BMI values too. It may be proper scientific research, and saying something like ‘a high BMI is correlated with low levels of dementia’ when reporting a study may not be a lie – but it doesn’t tell us the full and detailed picture.
So oversimplifications can lead to misleading advice. However, is it better to oversimplify an issue so that at least many people will watch or read about it, than explain something complex in full so that most people won’t even bother to watch or read it at all?
Media headlines often over-generalise findings from quite specific findings e.g. a headline may read ‘people who play videogames are good at x’ but we really need to take into account which specific games the study examined because there are so many different genres. So one study can claim that videogames are harmful while another can claim that they’re beneficial, and both can present valid points because they could be talking about different games or aspects – if only we look beyond the headlines and don’t instantly react to them according to our own preconceived, or desired, conclusions. Delve even deeper and it may even show a difference in average results between young and old people, males and females, etc.?
It’s critical to read the details of news stories in general because the headlines are frequently sensationalised. Headlines asserting ‘the truth about…’ aren’t always truthful. Video titles claiming ‘amazing facts…’ aren’t always factual! ‘You’ll never believe…’ or ‘find out the secret of…’ are classic clickbait headlines. We won’t know what’s interesting until we click on something and check it out… but when we do, much of the time we realise we’ve just wasted our time.
Some results should never be condensed into a neat, terse headline I reckon e.g. a study may show that a drug has a 70% success rate hence the conclusion is that it overall works. But the 30% failure rate shouldn’t be ignored (nor the rate and severity of any adverse side-effects). So something that is regarded as ‘a fact’ might only be a fact for 70% of cases. Rare fluffy outliers often exist too, although don’t presume a particular case will be one without appropriate supportive reason.
One TV commercial for a cosmetic product stated that ‘the average of 86% of participants agreed that the product worked for them’. What is this saying? Why were an arbitrary 14% of the opinions excluded when calculating the average?! They probably would’ve brought the average score way down? This is one example of how data can be distorted to fit almost any desired conclusion without lying. Well perhaps concealing part of the truth should be regarded as just as devious as directly lying in certain contexts like marketing? That’s why it often helps to peruse all of the data instead of just summary statistics, and then to make up our minds from that.
We may hear statements like ‘the wettest year for 250 years’ and then think that 250 years ago, before mass industrialisation, there was at least one year that was wetter than today hence today’s climate change is just natural variation. But this statistic on its own fails to convey how we’re seeing more consistently extreme weather events every year – each year may not be a record-breaker but each year of late has seen an increasingly high number of extreme weather events around the world.
Medians are often more informative than averages due to the effects of outliers e.g. how much couples spend on weddings. When we see average figures for such things, we might think we must meet this figure otherwise we’ll be considered ‘abnormal’ too. And if we all fall for this trap and chase trying to be ‘at least average’, we’ll just collectively push the average up ever further! This often means a race to ever-unsustainable levels of consumption.
25 million people may not have voted for Candidate A, which may be more than the 12 million people who did. But how many people did not vote for Candidate B compared to did?
And everybody’s a 10 – it just depends out of what(!) Woof!
It should be little surprise that e.g. a company that sells content creation software has published its own research that shows us that more than half of those who use their software monetise their content, because they want to promote their software. They may have twisted their definitions of things in ways that are favourable to them too? Even if what they publish is honest, they might’ve decided to hide other research that would’ve deprecated their own products? This would be akin to showing a highlights video of a basketball match where we only see the baskets that a team has scored and not any baskets that this team has conceded – they may have scored 75 points… but what if they had conceded 81? There are a lot of ways in which those with a biased interest can present a positive image of themselves. What is the truth without all of the truth?
Our own confirmation biases may also unconsciously interpret the words ‘may’ or ‘could’ as ‘definitely’ or ‘will’. We read a sticker on a toiletry product in a shop that says ‘clinically proven’ – but for what? Does the product actually do anything amazing to justify its higher price tag or is it only clinically proven to not do any harm, which, although important, is a very low bar (one that plain water would also pass!)
So read and scrutinise every science – or really every kind of – news article or marketing claim carefully and thoroughly, and perhaps read them more than once. Assumptions, exceptions and caveats to a finding are sometimes only presented near the bottoms of articles. Ask what is the main research question? What is the main method used in the study? What is the main result of the study (for instance is it only correlational)? What is the conclusion reached by the scientists (not the interpretations given by any journalists)? Then ask is there journalistic accuracy in the description or interpretation? Also ask if there are possible problems or limitations to the scientific study? And are other interpretations of the data possible?
Some science is conducted better than others. Even when well conducted – chance results can happen even if there’s only a remote chance of them happening.
If we don’t review science news in the media with our own critical thinking, we might weirdly strictly believe that our kids must play the part of Mary or Joseph in Christmas nativity plays because there’s a data link, historically, that kids who did so have on average earned more when they grew up compared to playing other roles. There’ll be a statistic that teams with a certain main colour for their home kits have won more trophies than teams with other colours historically. There’ll statistically be a certain first letter that has been historically linked with more successful companies than any other. And so on. But correlation doesn’t necessarily indicate causation, the causal direction may be reversed, or there could be a third factor that causes both variables? And the past doesn’t necessarily predict the future.
“It’s science” one might proclaim and, “We must obey the science.” Yes but we need to comprehend the finer details of the methodology and the confidence and spread of the results when averages are presented, for example, plus cogitate on how a study fits into the overall literature on the subject of other factors that affect future earnings or success?
Are you and/or the journalist misreading probability for destiny, or the past for the future? It’s perhaps a simple mainstream media-friendly ‘fun fact’ that makes us sound clever if we quote it, but not all information or knowledge is equal – some information is more useful to know than others.
Commonly in science news articles or documentaries, the front is loaded with definite-sounding claims and will start by presenting the supporting evidence for them – but only in the very last paragraph or minute will it state that the claims are actually ‘inconclusive’ or ‘further research is required’. Some media outlets are more culpable than others but the headlines or video titles and thumbnails are designed to lure you in like a pig to a sandwich or to inflame a reaction, more than act as clear and honest summaries of their content.
As storytelling creatures, people may even sensationalise narratives about how particular scientific discoveries were uncovered, such as an apple hitting Isaac Newton on the head.
Even when a scientific consensus is well-supported and stable, many of us don’t listen to or want to follow the science anyway, like that a well-balanced diet along with regular physical exercise is the answer to preventing many health problems – because what we really want to hear is what we want to hear e.g. that some sustainable ‘quick-fix’ diet really does exist!
…We should always be sceptical and critical. Yet at the end of the day, we must make decisions so that we can live our lives e.g. whether to eat ultra-processed meat or not. And we should make our decisions based on the best of everything that we currently scientifically know and for our own present circumstances, and then refine or adapt as we learn more if and when there is more to learn.
The less ideal attitude is to make a big smug deal about hearing others make mistakes or change their minds. This will make us stubbornly deny ever making mistakes or wanting to change our minds. Even the brightest ever minds have made mistakes, have admitted to making them and have changed their minds as necessary. It’s all part of the process of science, and of personal growth. But we often criticise politicians for being stubborn, then the next minute criticise them for u-turning(!)
We can think we’re adequately clued-up after listening to satire and a few catchy sound bites. But I’d say that mass media sources supplement a formal education on a complex subject rather than can ever replace one. After all, what’s the value of studying at a university or caring about qualifications if one can just read and watch a few things online and be just as clued-up?(!)
Informing and educating competes with being attention-grabbing and entertaining – for which being the latter is usually more financially rewarding. It’s about both supply and demand, as Fluffystealthkitten said in Post No.: 0881. We as media consumers mostly want to laugh, gossip or judge others than to learn; and even when we want to learn, we’re drawn to cognitive ease because (over)simplistic debates make us feel smart and therefore good about ourselves. Political discourse tends to therefore dumb-down on social media and descend into black-or-white polarised stances rather than complex nuance.
Woof.
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