Quirks and Quarks - How to battle climate apathy, and more stories about humans

Episode Date: August 28, 2026

From doubting our doubts to sleuthing out scientific fraud, this week we revisit some of our favourite stories about humans.

Hi, I'm Jamie Plesson. And every weekday, I host a news podcast called Front Burner. We do one story a day and try to give you a deep but not overwhelming amount of information in context. Think of us as a show that pulls lots of story threads together so you don't lose the plot. We're here to help you learn how all of these threads fit together. Follow Front Burner wherever you get your podcasts. This is a CBC podcast. Hi, I'm Bob McDonald. Welcome to the best of course. and quarks. On this week's show, we peel back the layers of what it means to be human. We start with a story from January about how to beat self-doubt. We also hear about why our brains tune out the climate crisis, and if when I look at green and you look at green, we're both seeing the same green. We'll uncover a widespread network of scientific fraud that threatens the trust we have in science, and will navigate across rough Arctic oceans to the Kitsisut Islands near Greenland, where ancient Inuit seafaring communities hunted and camped 4,500 years ago.

All this today on the best of Quarks and Quarks. When we set out to become the best versions of ourselves, our own doubts are often our worst enemy. Maybe you want to eat better, drink less, or exercise more to become healthier overall. But sticking to new habits to achieve our long-term goals can be notoriously difficult. Dr. Patrick Carroll wanted to find out why, so he started investigating how much confidence we need to meet our goals. And since having doubts can stop you from reaching your goals, he wondered what can stop self-doubt. And the surprising answer is, more doubt.

Dr. Carroll is a professor of psychology at Ohio State University at Lima. Hello and welcome to Quarks and Quarks. First of all, what were you hoping to look at in your study? Well, in my previous research, as you mentioned, I had shown that doubt really kills commitment to goals. And so I began asking the question of what might kill doubt. I came across some interesting research that was done at Ohio State University where you can have doubt at two levels. You can kind of think about it as a self-assified. attribute, and that's just a plain thought, no different from I like ice cream. But like all

thoughts, you could hold them with either confidence or doubt. So it's ironic that doubt can apply to anything, including doubt itself. You mentioned that there's two kinds of doubt. Yes. Now, the first one I understand, okay, I'm not sure I can do this, whatever's before me, but what's the second time? It's called metacognitive doubt. And, And you can think about cognition as a thought, like I have doubts about this goal. But we can vary in just how sure or unsure we are of those thoughts. And that has big implications for whether we use those thoughts or not. So metacognitive doubt is a subjective sense of certainty or uncertainty of the thought that you're holding.

When you talk about goals in your study, what goals did you focus on? Your most important personal goal. So we left it up to them to decide what goal to think of. For the most part, I think that those are the ones that really guide us over the long term. So like, what, I want to be an astronaut one day? Exactly. And those are the types of goals that do come out is I want to become a doctor, I want to become an astronaut. you know, butcher baker candlestick maker. Okay. Or in other words, to be a better version of

ourselves or a healthier version of ourselves. Exactly. Well, how did you go about studying this? Well, I did two studies. The first study was with an online sample. So all ages, all ethnicities, you know, different walks of life, the political spectrum. And we, had them fill out a scale designed to measure their doubts in their most, their most personally important goal. We then asked them to think about a time when they had experienced doubt or confidence in their thinking. And then we just simply asked them to rate their commitment to their most important personal goal. And what we found was consistently the same thing. Those who had higher goal doubts and it thought about a time that they were confident, they were less committed

to their goal. But for those who had doubts and wrote about a time when they felt doubtful, they actually showed higher commitment to their goals. Wow. So it was really an ironic effect. Yeah, it is. You would think that if you're thinking about your doubts, you'd reinforce them. but you're saying that doubting your doubt actually reduces the doubt. It's like a double negative here. Exactly. It is shown you would think it'd be additive. That is doubt plus doubt equals more doubt. But in fact, what you show is the reverse. It's non-additive. So doubt plus doubt equals less doubt. Wow. So what was the second part of your study? Second part of the study, we took a student sample. Because presumably,

there at a point in their life where they're thinking about those, you know, personally important goals. And we asked them to fill out the scale measuring their goal doubts. But this time, what we did to manipulate metacognitive doubt is we drew from prior research suggesting you can do it by getting people to write their thoughts with their non-dominate hand. And it's a line of work called, embodiment research. Essentially, people use their own bodily movements as cues to infer the validity of the thoughts they have in mind. So they take their shaky handwriting with their non-dominant hand as a cue, that their thoughts, that is the doubts they're writing out, must be invalid. and thereby they hold them with less confidence or more doubt.

And what did you find when you looked at their confidence? So we took a measure of commitment to the goals at the very end, and we showed that whereas confidence in their doubts went down, commitment to their goals went up. And so they're holding less confidence in their own doubt. And these are the people that wrote with their non-dominant hand. So their handwriting was terrible when they looked at it. And their confidence went up.

Yeah. Well, how powerful a tool do you think inducing doubts into your doubts can be in helping us achieve our goals? Well, I think it can be pretty powerful. You know, it's a simple technique. Parents, counselors, peers, friends can, you know, do this in others and get, you know, these ironic effects of greater commitment under conditions of initial doubt. Is there anything that we can do at home to apply this principle? It's kind of

a hotly debated topic whether you can do it to yourself. But, you know, write out your doubts with your non-dominate hand and, you know, kind of see how it feels. Or if you know, if you know, someone who doubts whether they can achieve their goals, like a parent, knows their kid has doubts about whether they can achieve their goals. If you just tell them, just write this out with your non-dominate hand or shake your head while you're writing it out as if to say no. We use that cue as well to indicate that our thoughts aren't valid. I think you could have some pretty big effects. And it's not like it costs any money to do. So if you don't believe you can get something done, look at the reasons why you believe that and doubt that.

Yeah. Dr. Carroll, thank you so much for your time. Well, thank you, Bob. I appreciate it. Dr. Patrick Carroll is a professor of psychology at Ohio State University at Lima. Ten years on from the Paris Pledge to limit global warming to 1.5 degrees a sobering message. President Lula, you have called this the copy. of truth. I could not agree more. And the hard truth is that we have failed to ensure we remain below

1.5 degrees. That was CBC's Susan Ormiston, reporting from the COP 30 Climate Summit in Brazil. In his opening remarks, UN Secretary General Antonio Gutierrez had strong words about our future if we don't limit our carbon emissions. It could push ecosystems past irreversible tipping points expose billions to unlivable conditions and amplify threats to peace and security. Every fraction of a degree means more hunger, displacement and loss, especially for those least responsible. This is moral failure and deadly negligence. It's a powerful message, the kind we've heard many times before. Yet the latest figures from the Global Carbon Project show we are on track to emit more carbon,

dioxide from fossil fuels this year than ever before. And despite the barrage of natural disasters we've seen, like wildfires, hurricanes, and floods, many are simply tuning out the climate crisis. Like the proverbial frog in a pot of boiling water, it's getting hot so gradually we stop paying attention. And this is something Dr. Ratchett Dubay wanted to investigate, to see if there's a better way we can communicate the urgency of this crisis. Dr. Dubay is a computational cognitive scientist and assistant professor at the University of California, Los Angeles. Hello and welcome to our program. Hi, Bob. Thank you for having me. What may you realize that we might be that frog in a pot of boiling water? That is a good question. I think for me, one of the most interesting data that I've seen

is that belief in climate change, I'm talking mostly about America right now, but belief in climate change in America has been steadily rising in the past 10 to 15 years. So more and more people are believing that climate change is real and it's happening. More people are also getting worried about climate change in general. It's not at a big level, but it's rising a little bit.

But the most interesting graphs for me and the data for me is that the percentage of people across all, political aisles that say that climate change is an important issue for them and it's a voting issue for them has remained relatively stable at around 35% to maximum 40%. So climate change was just not a talking point in the last election in America. It's still not a talking point in most of the local elections that's going on. So I think that to me is a very interesting aspect that's going on, right? So people believe climate change is happening. People somehow think that climate change will be bad for America or for the rest of the world, but it's just not a voting issue.

people don't care about climate change. And that has just remained steady in the last 10 to 20 years. So I think that to me was the first aspect that I just found super puzzling and super important to study. So how did you study this effect? So in this study, what we found was that when we present people temperature data, like when we show how the temperature has changed in the past 50 years, 200 years, for different towns across Europe and America, and we showed them that rising trend over a period of time,

and we asked them, how worried are you about climate change and how important do you think climate change is an issue? People think, you know, it's kind of an important issue, maybe they're slightly worried about climate change. But when we presented the same underlying trend in a different format, in a discrete format, where we presented people how much the local lake in a particular town has changed over a period of time, whether or not it used to freeze and does it freeze now.

Then people's worry and urgency about climate change was significantly higher when they were present at the temperature data. You know, maybe in the 1940s, 1980s, it used to freeze a lot, but now it doesn't freeze as much. When people see this, it gives them this kind of thing like, oh, things have really changed, right? It used to happen, something used to be good,

and now it's not good anymore. Whereas when we are presenting people, this temperature data, and I would argue, like when we talk about carbon dioxide emissions and things like that, it is very abstract in a perception. Right? Like, you know, it's getting harder, so what, right? But when we help people recognize and understand that climate change is already affecting their lives right now,

it will affect their lives in personal, dramatic consequences. Then people sit up and take more notice about climate change. So why does that affect happen? Why the lake freezing would snap people out of this, seeing climate change as a new normal? I would say there are two aspects to it. So that's the mere fact that I'm talking about lake freeze, right? You're already kind of imagining, you know, back in your childhood days, you could go to your local lake, you could maybe go ice skiing, there was a bit of a winter tradition about it, and now that's loss. Right.

When I'm talking about a lake used to freeze, a lake doesn't freeze, you're immediately doing some kind of vivid mental imagery about this scenario. When I'm talking about temperature, there's probably not much concrete imagination that you're doing when I'm talking about temperature. carbon emissions. The other aspect to it is people think that things have suddenly changed when we talk about lake freeze. Even though this change in the lake freeze has been gradual in our perception, right? Like, it's not like until 1980, it always used to freeze and then suddenly after 1980s stopped freezing. You know, there are some years where they were to freeze, you know, that's natural variation. That will also happen, right? But this lake freeze aspect snaps us out of this. Things are slowly, slowly changing, but it's like, oh, things have

suddenly dramatically changed. So why do you think we humans tend to do this to sort of adapt to things? Basically, what happening with climate change is our minds are gaslighting us into thinking it's not a big deal. Even though I've been working on climate change five to ten years almost now, I still sometimes think it's going to be okay. And what happens with climate change is that if you look at in the last 50 years or last 100 years, the rate at which we have emitted carbon in the atmosphere is unprecedented and insane. But in our daily perception, in our window of cognition with our limited memories and a limited attention span, climate change is only leading to slow and gradual changes in daily weather.

So there will be some days that are particularly warm. There will be some winters that are particularly warmer and maybe lake has not frozen or something like that. But in our daily experiences, climate change is not leading to drastic changes instantly right now. In our small window perception, climate change seems very. slow and very gradual. Even though, you know, if I was to magically transport you 30 years in the past, you would be absolutely blown away by how different, you know, your summers used to be and our winters used to be. And I would say that this argument also applies to other aspects to, right, like rising inequality, our adaptation to gun violence or political violence

for that matter too. Right. So that, I think, is the biggest tragedy of climate change. That it's happening really fast in Earth cycle, but in our perception, it's happening way too slowly. Now, beyond the freezing lake analogy, I understand that you were in Los Angeles during the terrible wildfires, the beginning of 2025. What did you experience? I was. I just moved to L.A. I could see the fires from my balcony, actually. We were just at the edge of the evacuation warning sign, but we decided to evacuate when the ashes were pouring down, basically.

It was pretty, pretty horrible. Very anxiety-inducing, too. I think I feel very lucky because if the winds had gone a different way, it could have been even more devastating than it was. So I think we had lucked out a bit over there. And we had to evacuate, and we were lucky enough that we had a set of friends that we could stay at their place for a week before we could come back to a place. So what would you say to a listener who's ready to surrender to climate change as a new normal

and has just tuned it out? I would say to the listeners is that there's a big difference between an earth that is warm by 2.5 degrees or 3 degrees. I do say that we need to use a kind of a binary framing to communicate about climate change. But I would encourage us to get away from a binary kind of thinking in terms of thinking about the consequences of climate change. We have to deal with the effects of climate change for the centuries to come now. It's not going to be the case that by 2100, we reach 2.5 degrees Celsius or 3 degrees Celsius and it's the end. That's not what's going to happen. Every degree of warming that we can prevent is going to save

countless lives and it's going to save countless number of sufferings. So if people are feeling hopeless about national level politics or international level politics, there's so much we can do at the local level. Make our towns more resilient to climate change. Connect to your neighbors. In terms of uncertainty, in terms of rising climate disasters, having a good, solid local base, you know, that supportive group that relies on each other, helps out each other, making a town that's resilient to flooding, there's resilient to climate disasters and has supportive infrastructure is really, really important. So I would encourage everyone to get involved in the

local politics as much as possible and build a strong local community. Dr. Dubay, thank you so much for your time. Thank you, Bob, so much. Dr. Rachat Dubay is a computational cognitive scientist and assistant professor at UCLA. This has always been one of my favorite scientific and maybe philosophical questions. Do you see what I see? For example, is your experience of the color red the same as mine? Well, a new study suggests that it is. Using brain imaging technology, scientists in Germany have determined that human brains respond essentially the same way to colors.

This startling discovery was made in part by Dr. Michael Bannert. He's a postdoctoral student with the Vision and Cognition Lab at Tubingen University in Germany. Hello and welcome to our show. Hello, thanks for inviting me. First of all, what colors did you use for this vision test? In our study, we used three colors that were easy to distinguish. That's why we used red, green, and yellow. Now, why did you choose those three?

We wanted to make sure that we have stable estimates of brain responses for the colors that we used. And this means that we have to deal with a trade-off. Either we show large numbers and have less reliance. estimates for each or we choose a small number of colors and have more reliable estimates to those few. So how did you record people's brain activity when they were looking at the colors? So the method that we use is called functional magnetic resonance imaging. And what it does is that it measures the magnetic properties of the blood in our brains.

and as parts of our brain become active during task execution, this means that energy consumption changes in certain areas, and the consumption of energy leads to a change in the magnetic properties of the neural tissue, and that's what we can measure with fMRI. Now, the fMRI machine, that's that giant donut that a person has to lie on a slab and put their head into the hole in the center. Is that it? Yes, right, exactly. So how does that setup work?

They've got their head in this big machine. How are they seeing the colors? So the colors are projected onto a screen that's presented at the end of the tube on a screen. And people have their heads in a head cage. And on top of this head cage, there's a mirror. And that allows them to, while lying on their backs on the scanner, to see what's at the end of the tube, so to speak. Of course, there's not enough space for a monitor to fit into an MRI machine.

And also, it is highly magnetic, too. So it will also be a danger to the participants if we put anything magnetic into the scanner room. So we need to work with this projection setup. What did you see happening in these people's brains when they were looking at the different colors? So what we saw was that different colors elicit different patterns of brain activity in each individual brain. And these differences in

patterns were so strong that you could predict what color a person was seeing after training a computer model based on the brain patterns from that same subject, but recorded at a different time. This is not new. So this had been done before. What's new in our study, though, is that we showed that it is possible to distinguish brain responses based on color from a subset of our subjects and then predict what color a person is seeing based on their brain activity that had never been used in training that classifier. And this suggests that some of these differences between the colors are preserved across different brains.

Okay, so let me see if I got this right. You're saying that you put people in the scanner, they looked at colors, you saw patterns appear in their brains, then you looked at patterns in these other people's brains and said, okay, they're looking at red. Is that how it works? Yeah, yeah. Yeah. So the challenge was just to get the computer model that was used to classify these brain responses

to predict it across brains. This was really the key to get this color cross-decoding going. Well, what does this tell us about the way our brains work? One, yes, to different brains, there's a tendency. for the same colors to look roughly the same or similar, I would say, certainly similar enough in order to allow you to predict what color a person is seeing based on color responses from other brains. So to that extent, they are similar.

That does not mean that there aren't any differences. And the second lesson, I think, that we learned from this is that the reason we can cross-decode colors between brains is that there seems to be a systematic, relationship between the way that our brains encode visual space and the way color is encoded in those same brains. But basically you're saying that if you and I both look at the color red, the response in our brains will essentially be the same, the same patterns. Similar, similar, not the same, but yeah, similar enough.

And if you want to get an idea of just how sensitive the human eye is to color, just go to a paint store. Look at all the chips of paint that are on the wall. colors you can choose from. It's amazing how many hundreds of them there are. Yeah, yeah. Dr. Banner, thank you so much for your time. Thank you very much. Dr. Michael Bannert is a postdoctoral student with the Vision and Cognition Lab at Tewiggin University in Germany. I'm Bob McDonald and you're listening to the best of Quarks and Quarks on CBC Radio 1 and streaming live on the CBC News app. Just go to the local tab and press play

wherever you are. most famous circus. The real balancing act is offstage. It's so big and so much pressure and we take more risk. Follow eight Cirque to Soleil performers as they juggle life and work. You have to sacrifice a lot of things like to leave your dream far from the people that you love. Where risk is part of the routine. We perform with no lines, no safety net, no nothing. Cirque Life, new docu-series. Stream now on CBC Gem. The science publishing business is an esoteric but vital part of the scientific process, but it's facing a huge challenge, organized fraud. What's supposed to happen is that scientists research something and submit their findings to a journal.

The journal editors recruit other scientists who work in that field to scrutinize the paper for issues or problems with its method or argument. Sometimes it's sent back to the authors for revision. And then ultimately, the reviewers recommend it be accepted or rejected for publication. This is a big part of how scientists share their findings with each other and the world. While over the summer, a study came out that shaking the very foundations of integrity in science. Scientists analyzing many thousands of retracted and suspicious studies, documented on sites like Retraction Watch and PubPier,

have uncovered a widespread network of science. scientific fraud that threatens the very trust we have in science. Dr. Reese Richardson led the work. For him, this all started when he and a colleague began looking into why scientists decide to study certain genes. What ensued from there took him down a rabbit hole of shady science so deep that he hasn't looked back since. Dr. Richardson is a postdoctoral fellow in meta-science and computational biology at Northwestern University in Chicago. Welcome to our program. Thanks for having me, Bob.

First of all, tell me what you saw when you first became suspicious about the extent of this publication problem that you saw in this paper. Right. So part of my research has to do with why people study particular genes. There are a lot of genes in the genome. Most of them are completely understudied. And a small number of them receive a lot of attention. So we noticed that there was a particular class of genes, namely, micro RNAs. The discovery of microRNAs actually won the Nobel Prize in medicine last year.

And we noticed that microRNAs had suddenly become very, very popular, but that the people that were publishing on them tended to all be from the same place, largely from hospitals in China, and they seemed to be publishing in the same journals. And the articles seem to be quite similar, as if they had been written from the same template. And as it turns out, many of them had. And that's sort of how we got started on this. Can you give me an example of some of the similarities that you saw? If you read the titles alone, it almost read like a madlib where you could select a particular cancer, a particular gene and a particular pathway.

So it would say something like gene A targets gene B in a particular gene. cancer C via pathway D or gene A does this in this cancer via this axis. And we started to pick out some of them just based on that. But also people started to notice that these publications tend to all feature the same images in them, not just in style, but completely identical images in papers that are from different institutions, from different authors on different cancers published at different times. Wow. So it's not just similarities, but outright identical patterns between these articles. Well, what did all these similarities between these studies tell you about how this was happening?

Right. So we had actually an existing collaboration with a researcher at the University of Sydney in Australia named Jennifer. for Byrne, and she's one of the co-authors on this study. And Jenny introduced us to the idea of paper mills. Have you heard of paper mills before? Well, you can explain it to me. Yeah, certainly. They've really only been documented in the last 10 or 15 years, but these organizations, for what we know about them, are thought to write papers at scale, largely from templates, and then sell authorship positions on those papers to scientists that wants a credit on their resume. They want to appear as more productive scientists or their employer is requiring them to publish in addition to practicing medicine or teaching or any of their other responsibilities.

Oh, I see. So is this the issue of publish or perish? Oh, yeah, no, yeah. That's exactly what we're talking about. Okay. Papers are basically like currency in science. So it helps a lot if you're trying to get promoted, if you're trying to get hired, if you're trying to keep your job to have papers. Some universities, for instance, this is very commonplace in places like India and Pakistan and was recently made illegal in China. Some universities will actually offer cash bonuses if you publish a paper in a prestigious enough venue. So there's a lot of incentives to get people to put out papers.

that are not good. And this huge industry has sprung up to take advantage of that. Okay. So these paper mills are producing fake paper. Are they using AI to produce these fake papers? For the majority of the time period that we look at, generative AI models like ChatGPT were not widely available. So it's likely that somebody was actually writing these from a template and grabbing text from one place and grabbing images from another. But with the advent of generative AI, this is probably going to accelerate quite a bit because it lowers the barrier for entry into writing scientific papers significantly.

So who's behind the fraud? Right. So that's a big unknown that we're not really sure about in many cases. There have been a lot of journalistic exposés of paper mills and how they work. Many are based in India. Some are based in China. There is one that was recently exposed by a colleague of ours that operates in Russia and Ukraine and around the former Soviet bloc. But their clientele can be basically anywhere. They're largely in countries where there are fewer opportunities to do legitimate research, but there's so little actually known about how big this industry is, what fields they operate in, etc., that we really,

don't know what the overall geographic extent of paper mill clientele is. Wow. Okay. So that's the paper mill producing the fake papers. Now, what about on the other side of it, the publications, the journals? So a lot of people assume that this is something that only happens in sort of backwater journals, stuff that nobody reads. That is not the case at all. These are journals that are owned by large European and North American publishers like Elsevier, like Springer Nature, like Wiley. And these products get cited quite often. We were able to collect a set of around 30,000 different paper mill products, largely

assembled by volunteer sleuths that were pouring through large amounts of the scientific literature at scale. And a lot of these paper mill products wind up having hundreds of citations on them, not just from other paper mill products, but from all around the scientific literature. And many of them are in high-impact journals, which traditionally the number of citations that a journal gets has been used to gauge how trustworthy that journal is. And that just doesn't work. Well, how did you go about uncovering the network behind these shady papers? Right. So we had a few different case studies in how these things operate. One of those case studies had to do with looking at papers that share the same images in them when they shouldn't be sharing the same images. And a lot of these observations have been recorded on a site called PubPear where scientists can comment on any scientific article. So we use PubPear comments to detail a network of more than 2,000. papers that all share images and thus probably all come from the same place.

Another case study, we actually did what I was calling digital archaeology, where we had this website of a paper mill based in India that was operating entirely out in the open, and they advertised to their clients which journals they could get you published in. And we cataloged over time using archived web pages how this list of journals had changed. And then we did a number of other case studies, like we looked at how editors can be involved in the publication of fraudulent science. We uncover dozens of editors at a handful of journals that were handling problematic papers way more often than you would expect by random chance. And many of those editors, either before our study or after have now been removed from their positions at these journals because they were

likely not just complicit but directly involved in schemes to publish fraudulent papers at scale. Well, besides using the same images, what other indicators did you have that these papers were fake and pumped out by paper mills? Right. So we talked about generative AI, right? But actually, there was even more rudimentary text generation stuff going on as early as like 2015. This is just one indicator that we use. But basically around 2015, a lot of journals started using text similarity software to check submissions for plagiarism.

And in response to that, people that wanted to plagiarize something started putting their plagiarized content through a paraphrasing engine that will swap out particular words. words. But this would lead to established scientific terms like breast cancer, for instance, being tortured into phrases like bosom disease, or P value becomes P esteem, or artificial intelligence becomes counterfeit consciousness. This phenomenon is called tortured phrases. There are thousands of them that have been discovered and documented on a site called the problematic paper screener. And the fact that these tortured phrases make it into the scientific literature not only suggest that the articles were probably plagiarized from somewhere,

but that nobody actually read them before they were published in a supposedly peer-reviewed outlet. So that is a strong indicator of paper mill involvement. Now, I know that in your study, you mostly focused on digging into the papers from the journal Plus 1.1. which does a lot of medical science. Why did you choose that one? So we chose Plus One for a couple of reasons. And this is just one of the case studies, right? We also examined Hindawi journals, which is imprint of Wiley that is now defunct.

It's since been closed because of paper mill infiltration. And we also looked at I-Triplee conferences. But the reason that we brought a lot of focus on Plus 1 in particular is because Plus 1 has historically had a large paper mill problem. There are to date around 1,000 publications that have been retracted in PLOS 1, many of which were for suspected paper mill involvement. But also because PLOS 1 is a journal that actually lists the editors that handle a particular article.

Most journals do not make that information available. And finally, PLOS actually makes all of the data associated. with those articles available to download at once. Most publishers don't do that. If you want to get access to high throughput data, you have to download things one article at a time. And that just wasn't what we were looking for. So PLOS really made a valuable case study for a number of reasons.

So when you put it all together, what did you see? How big a problem has this become? Right. So the full extent of the problem is chief among all unknowns here. But here's what we do know and what our study helps shed light on. Paper mills and networks underlying systematic fraud can be thousands of articles wide, hundreds of people wide, and they are robust organizations. And from the evidence that we've seen, they're probably growing.

And they also are very good at evading detection. They're very good at adapting to market pressures. And they very rarely see consequences. So we estimated that only around one and four paper mill products that make it into the peer-reviewed scientific literature will ever be retracted. Under all of these conditions, it suggests that we are in a perfect environment for growth of this industry. So when you say growing, any sense of how much? From the body of suspected paper mill products that we assembled, which again is probably just the tip of the iceberg, and there are definite biases in this corpus in time and in field, when you look at this corpus and its growth year over year, it looked like it was doubling in size every year and a half. For context, the scientific literature only doubles in size every 15 years.

That's a trend that has been consistent since the turn of the 20th century. In short, it looks like systematic fraud is outstripping the growth of overall science by orders of magnitude. Wow, that's astounding. Well, apart from the work to identify this by you and other scientists, what are the publishers of these scientific journals doing to control it? Good question. Very little. A lot of publishers have joined together for initiatives. Like there's one called United to Act that is specifically publisher agreements to do more research on paper mills and to research strategies on how to attack them. But most publishers really aren't interested in attacking this problem head on, in part because these publishers, through the open access publishing, model it's called make money in proportion to the amount of papers that they publish. They don't

make money for papers that they don't publish or for papers that get retracted later. Moreover, many publishers employ ludicrously small integrity teams whose job it is to find papers like this and to investigate them and to correct the scientific record. So if all these fraudulent papers are out there, how challenging does this make it for honest scientists to do their work? It makes it really difficult, right? So for instance, we talked about microRNAs. The microRNA literature, broadly, the literature about all non-coding RNAs is rife with paper mill products.

And it makes it very difficult for people that are working in these fields to navigate the literature and to find plausible high. hypotheses to test or to look for things. When you're looking through the scientific literature, you're looking for people that have done investigative work that you do not have to repeat, right? You're looking for facts that you can build off of. You don't necessarily want to be doing things over, but it looks like there is a ton of misinformation, particularly in these specific fields. So it makes it really complicated for scientists that are just trying to do their jobs. So can this problem of fake scientific publications ever be reined in?

I'm very much an optimist. So I tend to believe that this is something that can be stopped. But it requires a concerted effort on all fronts. There are certain prerequisites that I think we need to meet if we're ever going to nip this in the bud. One of them is we need to get away from profit-based publishing. The scientific literature should be a public good. It should not be a marketplace. I also believe that we need to move away from quantitative indicators. So we talked about publisher parish. We should stop counting people's publications and citations to those publications as a marker of quality. And finally, we're all competing for an increasingly scarce pool of jobs and an increasingly scarce pool of resources. And efforts like that led by

the United States to cut funding to scientific infrastructure are only going to make that situation worse. So I believe we need to double tenfold multiply our societal investment in science if we really want a commitment to scientific integrity and truth. Dr. Richardson, Thank you so much for your time. Thank you, Bob. Dr. Reese Richardson is a postdoctoral fellow in meta-science and computational biology at Northwestern University in Chicago. A voyage to the remote Kitsasut Islands north of Greenland is a hazardous one even today.

That's partly because the small islands are situated in an unusual area in the high Arctic that never freezes. The only way there is to cross a 53-kilometer-search. stretch of unruly open water, regardless of the time of year. Yet, we know ancient humans were there thanks to archaeological evidence they left behind. But how far back does evidence of humans on these islands go? Well, scientists from Greenland and Canada, with the help of local community members and hunters, went to investigate. And they discovered hundreds of archaeological features dating back to about 4,500 years ago, as well as lasting impacts to the environment. Altogether, their findings shed new light on the paleo-inuit people's remarkable nautical

capabilities and the role they played as ecological engineers on the islands. Canadian Dr. Matthew Walsh was part of the team that went to Kitsasut. He's an associate professor of archaeology at the University of Calgary and led the study. Hello and welcome to Quarks and Quarks. Hello, Bob. Nice to join you. So take us to the Kitsy Sood Islands. What's it like there? Paint me a picture. Well, it's an incredible experience. When we went, I had spent many months looking at them through satellite imagery and things like that. And so I had sort of expected them to be kind of empty and barren. But actually, they're very busy places during the summer.

So there's a nesting colony of thick-billed mirror. It's a species of seabird that nest in the cliffs around the islands by the thousands. So it's a very loud place in the summer. And you can imagine it's 24-hour sunlight, so there's constant activity of the birds. And it's actually quite a lively place. Why doesn't the water freeze around these islands? It's what's called the Pallinia in the Arctic. These are areas where for a variety of local factors, the ice doesn't, or it has kind of a limited extent. And in this particular area, it's partly the geography.

You get this ice bridge that forms across what's called Smith Sound between Greenland and the Canada. And then you have a combination of wind and currents and a few other factors, but this creates an expanse of water that doesn't freeze throughout the winters. So you have a kind of refugia for sea mammals there, as well as very rich phytoplankton blooms that feed a very unique ecosystem. Now, if it's 53 kilometers from shore, can you actually see the islands from shore? Like, it makes you wonder why people would go there in the first place. Yeah, so on a very clear day you can see across to Greenland, and you can also see across the Canada on the other side,

but that's a very rare circumstance where you have clear weather. And that's partly because of the mixing of the currents. You often have fog banks and all kinds of weather in the area that makes them very rarely visible. But one thing that you can clue into is the movement of birds, which go out to the islands. And so I think there's always some indicator that there is something there. Well, once you got to the island, what kind of archaeological features did you find there?

Well, this was very striking for an archaeological crew because there's hundreds of features all over the beach ridges there. And these are quite small islands, so a couple hundred meters across. But everywhere you look, there's pieces of basically ancient campsites. So old tent rings, hearth features with charcoal still in them, and scatters of bone and artifacts, things like that. So lots of clues that people have been there. and return many times over. So what would they have been doing on such small islands with so many birds? Well, there's a few clues around that.

So the campsites themselves are located directly under the bird cliffs. So the birds are a very important reason why they're traveling out there. You can collect eggs and you can also hunt the birds as well. And indeed, we found scatters of bird bones associated with the features, including some of the bones that we used radiocarbon dating to get a better understanding of the time frame there. You mentioned some of the artifacts you found were tent rings. What are those?

Yeah, so from this period, there's very distinct tent rings. They're very small, if you can imagine, between three and five meters. And they have these, we call them axial features, which are basically stone features that run down the center of them. And then on both sides of the tent, you have sometimes different representations of different activities, so different types of stone tools or bone. tools, things like that.

So the rings define the outside of the tent, the size of the tent? Yeah, essentially it's a skin tent that you're pinning down to kind of keep it stable when there's wind and things like that. Oh, I see. It's like we use tent pegs today. They use stones to hold the tent tap. Exactly. What about the journey to the Kitsasud Islands?

I mean, 53 kilometers. What would that journey have been like for them? Yeah. So there's a few ways of that. estimating that, but we think, you know, at minimum, it would have been a trip of about 15 to 18 hours of very difficult paddling. You'd have to know an awful lot about the weather in order to be able to do that because if conditions change when you're halfway across, you could be in significant trouble being blown off course into Bath and Bay. And we know a little bit about the watercraft from the period because there are a couple sites in the Arctic where you just get small fragments. So these tend to be pieces of wooden frames that would have had a skin covering that you'd you can seal with fat. So something very similar to kayaks and oomiacs that later inuit communities use. So it probably would have been something fairly similar that they're using to travel out there.

But if you say that there's fog and there's currents, that also means some navigational skills. Yes, absolutely. So they'd have had to have a lot of knowledge about seafaring, essentially, which isn't quite how we really understood them prior to this discovery. The implication here is that they could certainly intercept sea mammals or seabirds and have reach across all these different components of the Pallinia system. Now, I understand you also had local hunters as part of your study. What did they teach you about the place?

Yes, absolutely. I should emphasize, too. I'm representing a team of people here with my collaborators, Mari Klaist and Paulina Knudsen from the University of Greenland. We do a lot of archaeological work with local community members. and it's really quite an experience traveling out to the islands with them as well because they know a lot about nuances of the environment and going feature by feature looking at these archaeological signatures,

they can tell you a lot about what they mean in terms of the decisions and lifeways that those people would have experienced. Now, usually when people go places, they have some kind of impact on the environment. Did these ancient Inuit impact the islands in any way? Yes, I think it probably a number of different ways. So just by virtue of hunting the birds and collecting eggs, they are related to their population dynamics. But another important feature that we often observe through things like satellite imagery

is that they seem to have played a very important role in transferring nutrients from the sea to the landscape as well. And at this very early period, one of things we can see is that you get these little tiny clusters of vegetation in what otherwise is a polar desert. And those are often associated with either seabirds or archaeological sites. And so there's some sort of maybe collaborative engineering in terms of the growth and development of the terrestrial system. That is the vegetation and soils that are associated with these sites. They added vegetation or improved it? Well, I think by taking animals out of the sea and butchering them or doing all those kinds of activities around the campsite,

there's a transfer of nutrients, so things like phosphorus, nitrogen, carbon. And you can see these clustering of vegetation, even thousands of years later, where there's been a process of succession. They've become anchor points for the development of vegetation and then soils as a result of that as well. They fertilize the soil. Exactly. So what's your takeaway from this study in terms of our understanding of the paleo-inuit people in Greenland? Well, I think it opens up many great new questions about the long-term influence of those communities through time and maybe helps us. rethink some of the big questions in the presence around the co-management of some of these

areas between Greenland and Canada. So there is, I think, a very good argument within this for the kind of sustained and well-supported sovereignty of communities in terms of making environmental choices in this area. Dr. Walls, thank you so much for your time. Thank you very much, Bob. Pleasure to join you. Dr. Matthew Walls is a professor of archaeology at the University of Calgary. And that's it for the best of Quirks and Quarks this week. If you'd like to get in touch with us, our email is Quirx at cbc.ca. Our webpage is cbc.ca.ca slash Quarks, where you can check out our past episodes

and find more information on the research we covered in the show. You can also follow our podcast, get us on SiriusXM, or download the CBC Listen app. It's free from the App Store or Google Play. Quirx and Quarks is produced by Rosie Fernandez, Amanda Bukowitz, Sonia Biting, and Olivia Diring. Our senior producer is Hannah Hoag. I'm Bob McDonald. Thanks for listening. For more CBC podcasts, go to cbc.ca slash podcasts.