r/badscience • • Sep 01 '25

Tina Smith calls out bad science.

Post image
13.6k Upvotes

Health and Human Services Secretary Robert F. Kennedy Jr. claimed without evidence that antidepressants could have contributed to the mass shooting in Minnesota on Wednesday after an attacker opened fire on a church. The unsubstantiated antidepressant medication claim is another example of Kennedy floating ideas that contradict established science. It comes as Kennedy faces a mounting revolt at the CDC for his anti-vaccine views.

https://www.axios.com/2025/08/28/school-shooting-kennedy-antidepressants-claim


r/badscience • • Sep 01 '25

Scientist here.

Post image
3.8k Upvotes

r/badscience • • Jan 22 '25

Shall we ban twitter and X links from r/badscience?

1.8k Upvotes

The owner of X, formerly Twitter, appears to support Nazis. At Trump's innauguration, he twice saluted in a manner identical to fascist salutes. He is aware of the controversy and has had the opportunity to explain that it was not such a salute, but has not done so.

Many subreddits are now voting to ban /Twitter links. We should have a similar vote. Post a top-level comment saying yes, or no, as the first word. Only users who have posted or commented in /badscience previously will be counted. r/badscience is slower moving than many subreddits so I will leave the vote open for three whole days.

Edit: If you intend to vote make sure your comment is top-level and has yes or no as the first word.

Result: I make it 94 Yes, and 6 No. We don't get many posts or comments linking to Xitter, so its mainly symbolic, but it could stop some traffic and ad-revenue to a self-declared neo-Nazi. I'll add it as rule 6.


r/badscience • • Sep 06 '25

Anti-Vax RFK Jr. Plans to Blame Over-the-Counter Pain Medication for Autism

Thumbnail
thedailybeast.com
1.5k Upvotes

r/badscience • • Dec 06 '25

Actual comic book panel

Post image
1.4k Upvotes

r/badscience • • Jan 18 '21

I don’t have words honestly.

Post image
988 Upvotes

r/badscience • • Sep 03 '25

Paul Gosar has a novel solution to climate change

Post image
965 Upvotes

r/badscience • • Jan 16 '21

The great minds at r/dankmemes have a highly reductive answer to a hugely complex question

Post image
755 Upvotes

r/badscience • • Mar 06 '21

An acquaintance shared this image unironically as evidence against the rise of sea levels.

Post image
602 Upvotes

r/badscience • • Jan 19 '20

If you would, Senator, please circle the 'O' in 'CH4'

Post image
578 Upvotes

r/badscience • • Oct 24 '20

Bad science mesostics.

Post image
504 Upvotes

r/badscience • • Oct 12 '25

The planet has only warmed 2°F so nobody's suffering that much. BTW it's your fault if you die from extreme weather because you chose to live there

Post image
482 Upvotes

r/badscience • • Jan 23 '19

Debunking: 90% of land-based plastics comes from 10 rivers in Asia and Africa

473 Upvotes

This claim has been repeated by virtually all news outlets, so it's no wonder that it keeps resurfacing, like in this recent thread cross-posted to /r/bestof:

u/MajorMeerkats succinctly explains the sources of plastic waste in the world's oceans

I've debunked this many times, as you can see here, and I'm getting tired of it, so I wanted to do this once and for all.

First thing's first, this is the paper where the 90% claim stems from[1]:

Schmidt, C., Krauth, T., & Wagner, S. (2017). Export of Plastic Debris by Rivers into the Sea. Environmental Science & Technology, acs.est.7b02368. https://doi.org/10.1021/acs.est.7b02368

Now, if you read the title of the paper carefully, you'll have your first clue as to why the claim doesn't hold water. Rivers are one land source of plastics, but certainly not the only land source, nor the largest.

The abstract:

A substantial fraction of marine plastic debris originates from land-based sources and rivers potentially act as a major transport pathway for all sizes of plastic debris. We analyzed a global compilation of data on plastic debris in the water column across a wide range of river sizes. Plastic debris loads, both microplastic (particles <5 mm) and macroplastic (particles >5 mm) are positively related to the mismanaged plastic waste (MMPW) generated in the river catchments. This relationship is nonlinear where large rivers with  population-rich catchments delivering a disproportionately higher fraction of MMPW into the sea. The 10 top-ranked rivers transport 88–95% of the global load into the sea. Using MMPW as a predictor we calculate the global plastic debris inputs form rivers into the sea to range between 0.41 and 4 × 106 t/y. Due to the limited amount of data high uncertainties were expected and ultimately confirmed. The empirical analysis to quantify plastic loads in rivers can be extended easily by additional potential predictors other than MMPW, for example, hydrological conditions.

As we can see in the abstract above, the 90% claim stems directly from the paper, IF one forgets to keep in mind that the paper only assessed plastics from rivers. What the paper actually says is that of those 0.47 million tons to 2.75 million tons per year (the global annual river load into the sea), "the 10 top-ranked rivers transport 88−95%", not of the overall amount coming from land, let alone including maritime sources. We'll get to how significant this difference is in a bit.

Let's assume that the claim was true that 90% of plastic in the ocean comes from 10 rivers in Asia and Africa. First, for clarity, are we talking about 90% of plastics entering the ocean annually at the moment, or 90% of the total amount of plastic already in the ocean? Many headlines do not make a clear distinction, but there is an important difference. It's important because the current release might not reflect how the total amount got there in the past, when waste management practises in the West were much worse. This is comparable to how China is currently the world's largest emitter of greenhouse gasses, but USA and other western countries held this title for a long time before then, emitting most historical emissions. Remember, that old plastic is still around.

For simplicity's sake, let's focus on the annual land-based plastic release, because no one has a clear estimate of the total amount of plastic in the ocean. Land sources are estimated to account for 80% of plastics entering the ocean, whilst the remainder comes from maritime sources. This in itself excludes the possibility of 10 rivers exporting 90% of plastics entering the ocean, if one were to account for maritime sources as well, because - again - "only" 80% of plastics entering the ocean come from land.[2]

Now, if it were true that these rivers release 90% of land-based plastic, then if we look at estimates for the total annual release of land-based plastics, the figure for the amount of plastic coming from these 10 rivers would be 90% of that figure - right? Let's see.

Okay, we will use the most widely cited paper for the total land-based release of plastics[3]:Jambeck, J. R., Geyer, R., Wilcox, C., Siegler, T. R., Perryman, M., Andrady, A., … Lavender, K. (2015). Plastic waste inputs from land into the ocean. Science (Vol. 347). https://doi.org/10.1017/CBO9781107415386.010

Bearing in mind that this 2015 analysis was based on 2010 data, let's have a look at the numbers. So, according to Jambeck et al., between with 4.8 to 12.7 million tons of plastic are entering the ocean every year from land-based sources, so that's 4.8 × 106 and 12.7 × 106 tons/year. Okay, so how much plastic did Schmidt et al. 2017 estimate that rivers release into the ocean every year globally? In the abstract above, they report a range of 0.41 to 4 million tons annually, but wait - there's a catch! Schmidt et al. issued this correction, which almost no one took note of:

The numbers on the global plastic debris input from rivers provided in the abstract are incorrect. The correct version with the numbers from the Results section is: Using MMPW as a predictor we calculate the global plastic debris inputs form rivers into the sea to range between 0.47 × 106 and 2.75 × 106 t/y.

​So they lowered the upper end of their range as reported in the abstract from 4 million tons to 2.75 million tons.

For illustration, let's put the total land-based release and the river based release side by side:

Total annual land export of plastics into the ocean (Jambeck et al. 2015):

4.8 to 12.7 million tons

Total annual river export of plastics into the ocean (Schmidt et al. 2017):

0.41 to 2.75 million tons

Before we do the percentage calculation, does anyone wanna do some napkin math or take a wild guess if the lower (Schmidt et al.) number can ever be 90% of the upper (Jambeck et al.)? The answer is no.

Even if we compare the lower end of the former number and the upper end of the latter (which is a dubious thing to do), it gives no more than 57.3%. The middle of the 4.8 to 12.7 million tons / year, namely 8 million tons, is more commonly cited and used. Using this value, all rivers contribute between 5 and 34.4% of the total annual land-based input of plastics into the ocean, and 88-95% of this comes from 10 rivers. That means that the overall percentage of land-based plastics coming from these 10 rivers is somewhere between 4.5 and 31%. Possibly a substantial amount, but nowhere near the claimed 90%. It's worth noting that the authors of the river export paper emphasise the large uncertainty of their estimate in the abstract, as is evident from the fact that their upper estimate is 7 times higher than the lower estimate.

Just to drive the point home, let's look at the issue another way. 2.75 million tons is the upper end estimate for plastic entering the ocean each year through rivers. If this was 90% of the total input, what would the total be? Well, we would need to add 10% to get from 90% to 100%, right? Let's do that.

Total (plastic_input) * 0.9 = 2.75 * 106 tons

Total (plastic_input) = (2.75* 106 tons) / 0.9 = 3.06 * 106 tons or 3.06 million tons per year.

Voila! Now the issue of plastic pollution is 60% smaller than reported by virtually everyone (see links below).

If this were true, this would be the main finding of the Schmidt et. al paper!

Since this conclusion is so far off, it's evident that the premise that rivers (which export a maximum of 2.75 million tons of plastic into the sea per year) are "responsible for around 90 percent of the global input of plastic into the sea" is wrong.

I hope you will help me share this information, both in the linked thread and elsewhere, because this myth just won't die, despite my sustained efforts to kill it. It keeps popping up every time plastic pollution is discussed, polluting the debate.

If you want to read more, National Geographic and MarineLitter.no have also debunked this myth:

References:

[1]: Schmidt, C., Krauth, T., & Wagner, S. (2017). Export of Plastic Debris by Rivers into the Sea. Environmental Science & Technology, acs.est.7b02368. https://doi.org/10.1021/acs.est.7b02368[2]: Jambeck, J. R., Geyer, R., Wilcox, C., Siegler, T. R., Perryman, M., Andrady, A., … Lavender, K. (2015). Plastic waste inputs from land into the ocean. Science (Vol. 347). https://doi.org/10.1017/CBO9781107415386.010[3]: https://www.eunomia.co.uk/reports-tools/plastics-in-the-marine-environment/


r/badscience • • May 26 '21

These images prove...something.

Post image
468 Upvotes

r/badscience • • Sep 14 '20

Viruses don’t cause disease? Then what does?

Post image
463 Upvotes

r/badscience • • Mar 06 '20

"Female are superior" because of number of genes and size of chromosomes

Post image
461 Upvotes

r/badscience • • Feb 02 '21

Oh my! What a rare occurence

Post image
442 Upvotes

r/badscience • • Apr 26 '21

Damn scientists and their stupid new information changing their ideas.

Post image
439 Upvotes

r/badscience • • Mar 14 '20

Based upon my survey of gunshot victims, gunshot wounds are never fatal.

427 Upvotes

r/badscience • • Dec 16 '20

An /r/murderedbywords post that misses the mark

Post image
423 Upvotes

r/badscience • • Apr 05 '21

Phrenology is back with vengence! (not really)

Post image
396 Upvotes

r/badscience • • Dec 23 '24

I want my revelation to be taken seriously in the field of physics, but I don't want to do any math.

Thumbnail
gallery
390 Upvotes

r/badscience • • Apr 30 '20

A focused rebuttal to “race realism”- the belief that there is a large racial intelligence gap due to genetics- found in /r/badscience and elsewhere

381 Upvotes

There is an idea spreading on the internet that there are large racial IQ gaps- in particular the gap between white and black IQs- and that these gaps are predominantly due to genetic differences. Unfortunately, this idea has found many audiences on reddit, and there have been posts on this subreddit supporting that stance. Many of the people who advocate for race realism appear well-read and quote studies that seem to support their viewpoint. However, I believe that this ideology is not only extremely dangerous, but is also factually wrong. So, I will be devoting this post to bringing a wide range of evidence to disproving race realism.

First, I want to clarify a few of my positions before beginning my critique:

  1. I believe that the IQ test is a reliable and unbiased measure of a significant part of what most people define as intelligence in industrialized societies. While the test has a sordid history of racism and misuse, the most-used IQ tests (eg: the WISC and WAIS) have gone through great lengths in reducing cultural biases in its questions.

  2. There is no doubt that there is a racial gap in IQ: what I will be arguing is that this is primarily due to environmental- not genetic causes.

  3. Finally, I believe that- like with most things- intelligence is a product of both inherited traits and the environment. In this post, I will be arguing that genetic differences are not the predominant explaining factor for the racial intelligence gap.

With my starting stances out of the way, let us begin:

A. Evidence from Racial Admixture studies

We benefit from having an African American population in the United States with a wide range of mixed European ancestry. This means we can have a powerful test of the hereditarian hypothesis. If the hereditarian hypothesis accurately explains the difference in Black-White IQ, then African Americans with greater European ancestry should have higher IQs then African Americans with less European ancestry. So, what does the data show?

I will first present a study which recruited black twins from 181 different families in Philadelphia. Using blood group markers, the researchers were able to estimated the percent Caucasian ancestry of the kids before having them take a variety of intelligence tests. They found that there was absolutely no correlation between white ancestry and intelligence. [1]

A separate study used skin color as an estimate of Caucasian ancestry and looked at 437 African American participants’ performance on a 10-point vocabulary test. The study found no correlation between skin tone and test performance when controlled for family and childhood educational background [2].

At the risk of beating a dead horse, I will look at one last racial admixture study to cement my point. In this study, researchers looked at black, mixed, and white kids adopted by either black or white middle class families. Mixed was defined as the child having one black and one white parent. The researchers (again) found no difference between black and mixed-race children in IQ as measured by WISC. However, even more interesting is that kids adopted to white families had significantly higher IQ scores than kids adopted to black families, suggesting a large environmental factor in producing differences in IQ. [3]

In order for the race realist argument to hold water, then there must be strong evidence that those who have greater European ancestry have a higher iq than those with less European ancestry. However, the various studies I have shown all disprove that argument.

B. Evidence from Twin Adoption Studies

This section will be structured more as a rebuttal than a point on its own, since race realists tend to rely heavily on twin adoption studies. The logic behind these studies run like this: monozygotic (identical) twins have the same genetic makeup, and adoption allows these twins to be placed in different environments. Therefore, the similarity in IQ between these twins who have been adopted into different households should be from a solely genetic origin. The logical throughline is strong, and race realists have used this experimental paradigm to arrive at IQ heritability values of around 0.85 or higher by adulthood.

This seems to be airtight, rigorous evidence for a high heritability of IQ. However, there is a large fault in a crucial assumption of twin studies: the assumption that the twins are adopted by families with very different backgrounds and live in very different environments. That assumption turns out to be false: Adoptive families tend to be more homogenous, with smaller variability of SES and HOME scores (used to measure the amount of intellectual stimulation present in a family environment). Indeed, a study that accounted for these variables found that the restricted variability of family environments in adoption studies could account for as much as 50% of the variance IQ found in these studies.[4]

C. Sub-Saharan IQ

Just as in part B, this section will be formatted as a rebuttal to a common argument of race realists: that the average Sub-Saharan IQ sits at a paltry 70. This IQ of 70 is the most commonly held number by the most prominent race realists such as Arthur Jensen and Richard Lynn [5]. One should be immediately skeptical of that number, seeing as that corresponds to a score a full two standard deviations below average. Put it another way, this would mean that the average person in Sub-Saharan Africa is less intelligent than 97% of people in America. So, what is the problem?

The problem lies with a variety of factors that all contribute to poor designs and biased results in the studies that race realists use to support their claim. The literature reviews tend to disregard relevant studies that show higher IQs, and the studies used tend to rely on convenience samples, which would not be relevant to the overall population. Finally, administering a western IQ test to a very different culture in developing nations poses many problems that make the tests less valid. Now, I have made broad attacks on the studies that race realists use without providing citations, and that is because there are several studies I would need to mention and this post is already extremely long. If anyone wants more specific information, I am more than happy to provide it in the comment section.

So, what is the best value we have for Sub-Saharan IQ? For that, I will rely on a systematic review of data on Sub-Saharan performance on Raven's Progressive Matrices. The inclusion criteria for this study was particularly rigorous, excluding any studies that did not adhere to administrative norms and found a value for IQ of...80, a full 10 points higher but still quite low when compared to that of industrialized nations [6]. However, there is still one factor to take into account: the Flynn Effect.

If the average Sub-Saharan African was compared to the average British person from 1948 you would find that their IQs would be identical [6]. As it turns out, There has been a steady increase in IQ over the 20th century in the industrialized world, a phenomenon called the Flynn Effect. Though the reasons are still unclear, the most common are improvements in children’s health, nutrition, and parental literacy, all of which agree with the limited correlational data we have [7]. Seeing as Sub-Saharan Africa is still the poorest region in the world, with poor food security and health infrastructure, it follows that we would see a corresponding Flynn Effect on African populations that mirrors that of the western world over the 20th century as Africa industrializes.

D. Modern Phrenology

Another core line of argument from race realists is the idea that brain volume correlates with intelligence. This argument is particularly enticing for two reasons: it presents a biological basis for heritable intelligence, and it has the intuitive reasoning that a larger brain means a smarter person. The issue is, as most people reading this can guess, the best data we have on the relationship between brain volume and intelligence is very minimal.

A meta-analysis of 88 studies on a combined >8000 individuals found that the relationship between brain volume and IQ has an R2 value of...0.06. Put it another way, brain volume explains 6% of the variation in IQ. That is an incredibly low number, and is completely inadequate as a biological basis for genetic causes of intelligence [8].

As a last line of evidence on this topic, I want to talk about sex differences in brain volume and IQ. We know that even when adjusted for height and weight, men tend to have a larger brain volume than women [9]. Therefore, if brain volume does correlate with intelligence, men should be more intelligent than women on average. However, the evidence for that is simply not there. Studies have argued men had lower IQs than women, women have higher IQs than men, and men having equal IQs to women. The best study that I can find, which looked at a nationally representative sample of UK kids and young adults, found no difference in IQ between men and women [10]. Again, the different lines of evidence just do not support the idea that larger brain volume means greater intelligence.

Concluding remarks:

The most popular lines of evidence race realists use to justify the hereditarian hypothesis (twin adoption studies, brain volume studies and cross-national IQ studies) all have deep methodological flaws or do not support their position. Moreover, racial admixture studies provide an extremely powerful contradiction to race realism: greater European ancestry in African Americans simply do not lead to greater IQs. I wrote this post not simply to critique race realism but to provide a wide variety of tools to argue against it, should you need them. I have seen first-hand how persuasive race realist arguments can be, and I think it is absolutely essential that more people should have the requisite knowledge to argue against an ideology that is sadly gaining ground.

I fully expect there to be race realists who will read this and critique it. I am more than willing to have a conversation with them, and I encourage everyone to avoid knee-jerk assertions of racism or personal insults.

References:

[1]Scarr, Sandra, et al. "Absence of a relationship between degree of White ancestry and intellectual skills within a Black population." Human genetics 39.1 (1977): 69-86.

[2] Hill, Mark E. "Skin color and intelligence in African Americans: A reanalysis of Lynn's data." Population and Environment 24.2 (2002): 209-214.

[3] Moore, Elsie G. "Family socialization and the IQ test performance of traditionally and transracially adopted Black children." Developmental psychology 22.3 (1986): 317.

[4] Stoolmiller, Mike. "Implications of the restricted range of family environments for estimates of heritability and nonshared environment in behavior–genetic adoption studies." Psychological bulletin 125.4 (1999): 392.

[5] Rushton, J. Philippe, and Arthur R. Jensen. "Race and IQ: A theory-based review of the research in Richard Nisbett's Intelligence and how to get it." The Open Psychology Journal (2010).

[6]Wicherts, Jelte M., et al. "Raven's test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn Effect." Learning and Individual Differences 20.3 (2010): 135-151.

[7] Daley, Tamara C., et al. “IQ on the Rise: The Flynn Effect in Rural Kenyan Children.” Psychological Science, vol. 14, no. 3, May 2003, pp. 215–219

[8] Pietschnig, Jakob, et al. "Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean?." Neuroscience & Biobehavioral Reviews 57 (2015): 411-432.

[9] Ruigrok, Amber NV, et al. "A meta-analysis of sex differences in human brain structure." Neuroscience & Biobehavioral Reviews 39 (2014): 34-50.

[10] Savage-McGlynn, Emily. "Sex differences in intelligence in younger and older participants of the Raven’s Standard Progressive Matrices Plus." Personality and Individual Differences 53.2 (2012): 137-141.