How not to convince a scientist that comic artists make good science communicators

Thanks to RationalWiki I found a blog post by a comic artist on science communication. It left me confused at several levels. As always I write the following not in any official capacity, and my opinion is mine alone and not necessarily shared by any person or institution I am affiliated with.

I don't know much about science, and even less about climate science.

This right here may well be the core problem of what follows.

So as a practical matter, I like to side with the majority of scientists until they change their collective minds. They might be wrong, but their guess is probably better than mine.

On the other hand, this is a very insightful paragraph. It would be helpful if we could all respect each other's expertise a bit more. Unless I have good reason not to, I assume that fully qualified primary school teachers know more about teaching primary school children than I do, plumbers know more about plumbing than I do, and so on.

That said, it is mind-boggling to me that the scientific community can't make a case for climate science that sounds convincing, even to some of the people on their side, such as me. In other words, I think scientists are right (because I play the odds), but I am puzzled by why they can't put together a convincing argument, whereas the skeptics can, and easily do. Shouldn't it be the other way around?

The implication is that it is the climate scientists' fault that there are climate change denialists, because scientists are poor communicators. Fair enough, many of us scientists probably could be better communicators. But in this context the argument only works if one assumes that everybody is rational and open to evidence in the first place. The fact is, it is just a really, really uncomfortable idea that our daily comforts like driving the car to work or cranking up air conditioning might be destroying our collective future. It is understandable that many people would reject such an idea regardless of how good a case could be made.

Whether denialists actually do make a better case than scientists is, of course, yet another matter. I do not think so, but then again, I am also a scientist, so I may not be representative.

As a public service, and to save the planet, obviously, I will tell you what it would take to convince skeptics that climate science is a problem that we must fix. Please avoid the following persuasion mistakes.

A comic book author telling scientists how to communicate science. Next up: a dentist telling comic artists how to draw, followed by a philosopher telling structural engineers how to design a bridge.

1. Stop telling me the "models" (plural) are good. If you told me one specific model was good, that might sound convincing. But if climate scientists have multiple models, and they all point in the same general direction, something sounds fishy. If climate science is relatively "settled," wouldn't we all use the same models and assumptions?

And why can't science tell me which one of the different models is the good one, so we can ignore the less-good ones? What's up with that? If you can't tell me which model is better than the others, why would I believe anything about them?

So as his first point the author assumes that there can only ever be one model in any area of science, and all the rest should be discarded. That is not how this works. That is not how any of this works. I am currently envisioning somebody applying the same logic to molecular phylogenetics: "If evolution was settled, wouldn't you all use the same model of character evolution? Why do you still have GTR, JC, F81, and all those other models?"

And how is it "fishy" if scientists have several models that "all point in the same general direction"? Logically, wouldn't the exact opposite look fishy, if each model lead to a different conclusion?

2. Stop telling me the climate models are excellent at hindcasting, meaning they work when you look at history. That is also true of financial models, and we know financial models can NOT predict the future. We also know that investment advisors like to show you their pure-luck past performance to scam you into thinking they can do it in the future. To put it bluntly, climate science is using the most well-known scam method (predicting the past) to gain credibility. That doesn't mean climate models are scams. It only means scientists picked the least credible way to claim credibility. Were there no options for presenting their case in a credible way?

Just to be clear, hindcasting is a necessary check-off for knowing your models are rational and worthy of testing in the future. But it tells you nothing of their ability to predict the future. If scientists were honest about that point, they would be more credible.

This seems more like a personal hang-up than a general problem. How many members of the general public will think "ah, the scientists say that their models work well if tested against past observations, but precisely that is a very good reason not to trust their capacity to predict the future"? Cannot imagine it would be many.

And I find the comparison with investment advisors a bit misguided; we are not talking stock performance here, where one tries to predict the future of one particular investment. We are talking something more comparable to macro-economic modeling, and while there is certainly a lot of motivated reasoning in economics such high-level processes can be predicted with some confidence. It would be hard to say where exactly IBM shares will be in two years, but it should be no problem to provide a prediction on whether inflation will go up or down if the central bank of a country prints a lot more money. (Even I know that increasing the amount of money raises inflation, all else being equal.) Likewise, it might be hard to say exactly how much rain Madrid will have in the year 2100, but it should be no problem to provide a prediction on whether temperature will go up or down if CO2 levels in the atmosphere are doubled, and by how much approximately. (Apparently up by between 1.5 and 4.5C.)

3. Tell me what percentage of warming is caused by humans versus natural causes. If humans are 10% of the cause, I am not so worried. If we are 90%, you have my attention. And if you leave out the percentage caused by humans, I have to assume the omission is intentional. And why would you leave out the most important number if you were being straight with people? Sounds fishy.

This is, again, very strange. If somebody says, "I will now push you over the cliff edge" they have your attention, but if they say "get back, quick, the cliff is crumbling under your feet!", you ignore them? What? I at least would say that even if warming were natural we should not ignore it but still prepare for flooded coastal cities and failed harvests.

There might be a good reason why science doesn't know the percentage of human-made warming and still has a good reason for being alarmed. I just haven't seen it, and I've been looking for it. Why would climate science ignore the only important fact for persuasion?

No idea where the idea comes from that climate science ignores this factor. It is widely agreed among the climate science community that humans are the main factor in what is currently happening, and in turn that expert consensus is widely known to exist.

Today I saw an article saying humans are responsible for MORE than 100% of warming because the earth would otherwise be in a cooling state. No links provided. Credibility = zero.

Why credibility = zero? Does the author not know that the earth underwent some noticeable cooling during the early modern period? Little ice age, anyone? There is also a good argument to be made, based on the timing of previous glacial cycles, that we are due for the start of another ice age, although of course such a change would take hundreds to thousands of years. I haven't looked into it deeply, but the idea that the earth would be cooling a bit if not for the use of fossil fuels is, in fact, at the very least credible to me given these considerations.

4. Stop attacking some of the messengers for believing that our reality holds evidence of Intelligent Design.

What "messengers"? What has any of this to do with Intelligent Design - where does that suddenly come from?

Climate science alarmists need to update their thinking to the "simulated universe" idea that makes a convincing case that we are a trillion times more likely to be a simulation than we are likely to be the first creatures who can create one. No God is required in that theory, and it is entirely compatible with accepted science. (Even if it is wrong.)

Ye gods, the simulated universe... Although I cannot find the link again I once read a very nice analogy for it. "Look, we can do simulations - so probably we are also simulated" is entirely equivalent to some Renaissance philosopher seeing the first paintings that used realistic perspective and concluding that because the real world also has perspective we must be paint pigments on another being's canvas.

It is all about getting caught up in enthusiasm about a new technology, with no evidence being involved anywhere along the chain of reasoning. There is no evidence that something like us could even be simulated, and it seems rather implausible that somebody would be motivated to run such a simulation. I guess one could play the mysterious ways card regarding the simulator's motivations, but then we are deeply in religious apologetics territory.

But still, the main point is that point #4 is completely besides the point.

5. Skeptics produce charts of the earth's temperature going up and down for ages before humans were industrialized. If you can't explain-away that chart, I can't hear anything else you say. I believe the climate alarmists are talking about the rate of increase, not the actual temperatures. But why do I never see their chart overlayed on the skeptics' chart so we can see the difference? That seems like the obvious thing to do. In fact, climate alarmists should throw out everything but that one chart.

Sorry to say, but reading this item I cannot help but think of the term Not Even Wrong. Of course temperatures go up and down naturally, so no scientist is ever going to "explain that away". The implied claim that climate scientists assume no non-anthropogenic climate change has ever taken place is shades of crocoduck, a ridiculous straw-man that would only be brought up by somebody who has not made the slightest effort at understanding the science in question. Scientific publications "produce" the very same charts of natural change, that is where the denialists get them from. The question is, do I have to "explain away" the fact that people die of natural causes all the time before I can object to somebody trying to kill me?

And why rates of increase? Of course a higher rate of change is a problem because it gives us less time to adapt and wildlife less time to move with their climate zone, but ultimately that is not all that "alarmists are talking about". Yes, if Miami is going to turn into Atlantis it may matter whether rates of change are different to, say, the onset of the current interglacial, but first and foremost it matters that the population of Miami will have to move, right?

6. Stop telling me the arctic ice on one pole is decreasing if you are ignoring the increase on the other pole. Or tell me why the experts observing the ice increase are wrong. When you ignore the claim, it feels fishy.

Maybe I missed something, but to the best of my understanding ice is shrinking on both poles. But even if this refers to some reference saying that ice is growing in some part of the Antarctic (a weblink would have been helpful), nobody would claim that every place on earth will experience the same effect with the same effect size. It is, for example, entirely to be expected that it will get drier in one place but wetter in another. In fact, the reason the former place is now drier is most likely that the rain it usually got is now falling in the latter place!

7. When skeptics point out that the Earth has not warmed as predicted, don't change the subject to sea levels. That sounds fishy.

This must either refer to some isolated incident that is not referenced or represent a misunderstanding: It sounds like a garbled version of the observation that the ocean has absorbed some of the warming that was expected to be absorbed by the atmosphere.

8. Don't let the skeptics talk last. The typical arc I see online is that Climate Scientists point out that temperatures are rising, then skeptics produce a chart saying the temperatures are always fluctuating, and have for as far as we can measure. If the real argument is about rate of change, stop telling me about record high temperatures as if they are proof of something.

This is merely a repeat of #5.

9. Stop pointing to record warmth in one place when we're also having record cold in others. How is one relevant and the other is not?

I already touched on this with regard to #6. North America seems to have unusually cold winters precisely because the north pole has unusually warm ones, due to shifting air currents. Truth be told, this objection really astonishes me. Some denialists sound as if they would be surprised by workplaces being empty at the same time as when beaches are full of people. "So are there more people or less people? You don't make sense!"

10. Don't tell me how well your models predict the past. Tell me how many climate models have ever been created, since we started doing this sort of thing, and tell me how many have now been discarded because they didn't predict correctly. If the answer is "All of the old ones failed and we were totally surprised because they were good at hindcasting," then why would I trust the new ones?

This is partly a repeat of #1 and partly a severe misunderstanding of how science works. "If Newton's theory of gravity was superseded by Einstein's theory, why should I now trust Einstein?"

Also, this.

11. When you claim the oceans have risen dramatically, you need to explain why insurance companies are ignoring this risk and why my local beaches look exactly the same to me.

To the best of my understanding, even Donald Trump's Irish golf course has lobbied the local government for a sea wall to protect against rising sea levels...

Also, when I Google this question, why are half of the top search results debunking the rise? How can I tell who is right? They all sound credible to me.

Yes, when I google about health, the search results variously suggest certified pharmaceuticals, homeopathy, reiki, acupuncture, chiropractics, and much more. There are quacks on one side and science-based medical research on the other. How can I tell who is right? I am so confused!

12. If you want me to believe warmer temperatures are bad, you need to produce a chart telling me how humankind thrived during various warmer and colder eras. Was warming usually good or usually bad?

You also need to convince me that economic models are accurate. Sure, we might have warming, but you have to run economic models to figure out how that affects things. And economic models are, as you know, usually worthless.

To be fair, the author may not realise that the last time global temperatures underwent several degrees of change we did not have billions of people living in coastal areas that are going to be flooded, or billions of people to be fed by crops that will suddenly find themselves under heat and drought stress.

13. Stop conflating the basic science and the measurements with the models. Each has its own credibility. The basic science and even the measurements are credible. The models are less so. If you don't make that distinction, I see the message as manipulation, not an honest transfer of knowledge.

Once more this probably refers to an unreferenced incident, so it is difficult to address. More generally, every mathematical description of a system is a model. If I say, "every day this plant grows 5 mm" I have formulated an (admittedly simplistic) model. It not sure how that is so much less credible than a chart showing the plant to have a stem height of 4.3 cm, 4.8 cm, and 5.3 cm on successive days. It is merely a different way of expressing the same pattern.

14. If skeptics make you retreat to Pascal's Wager as your main argument for aggressively responding the climate change, please understand that you lost the debate. The world is full of risks that might happen. We don't treat all of them as real. And we can't rank any of these risks to know how to allocate our capital to the best path. Should we put a trillion dollars into climate remediation or use that money for a missile defense system to better protect us from North Korea?

Yet another instance of what was presumably an unreferenced incident experienced by the author. I would not know how any serious climate scientists would ever have to propose Pascal's Wager, given that the action of CO2 as a greenhouse gas has been established for more than a century and that evidence of rising sea levels, shrinking glaciers, rising atmospheric temperatures, and increasingly extreme weather events are all around us. But then again, I am not even a climate scientist myself, so I don't know very much how they generally argue.

Anyway, to me it seems brutally wrong to call skeptics on climate science "anti-science" when all they want is for science to make its case in a way that doesn't look exactly like a financial scam.* Is that asking a lot?

This is a hilariously naive understanding of denialism. Sure, everybody everywhere is totally open to argument and merely "want[s] for science to make its case in a way that doesn't look exactly like a financial scam". Financial and political interests or tribal instincts do not exist. Riiight.

So in summary, I am sure that many scientists, me included, could learn a lot more about how to communicate. This post, however, was the equivalent of "hey medical profession, you could convince people not to use homeopathy if only you admitted that magic works, and you should stop all that double-blind experiment nonsense, because that just looks as if you have something to hide".

Species delimitation using the coalescent model

For two weeks or so now a new paper has been making the rounds, and we discussed it in our journal club today:

Sukumaran J, Knowles LL, 2017. Multispecies coalescent delimits structure, not species. PNAS 7: 1607-1612.

The context is species delimitation: given a bunch of individuals, how many species are there, and which individuals belong to which species? There are a number of ways to address these questions, and they partly depend on the available data and technology and partly on the species concept the researcher is using.

Very traditionally, of course, a taxonomist would look at the morphology of the specimens and more or less intuitively try to form clusters of similar specimens separated from each other by gaps in morphological variation. In other words, a qualitative application of the Genotypic Cluster Species Concept. More dubious approaches would involve ideal "types" (in a Platonic sense), "central identities", or rules of thumb on the lines of "one difference means subspecies, two differences means species", none of which seem to have much basis in what we know about genetics or evolutionary biology.

More formally, one can take the same theoretical approach but conduct an explicit, quantitative analysis. Score the morphological data and produce a pair-wise distance matrix for example with the Gower metric, then do a Principal Coordinates Analysis to visualise potential clusters and gaps between them, or do hierarchical or non-hierarchical clustering. The same can be done with non-morphological data, such as environmental data from the collecting localities, in that case to show that putative species have different ecological niches.

A clustering approach can also, of course, be used for genetic data. In that case one would use some kind of genotyping approach, for example microsatellites, AFLP or genome-wide SNPs, and do hierarchical clustering or use a software such as STRUCTURE. Although using a population genetics model, the results produced by the latter are at a practical level comparable to the non-hierarchical clustering in that we get an optimal number of clusters and information on what sample belongs to what cluster; we then need to make the additional interpretative step of assuming that the clusters are the species. (Meaning we have solved the grouping problem but need additional arguments to solve the ranking problem.)

But today more and more people have multi-locus sequence data at their disposal. They are used for phylogenetics under the coalescent model and using species tree approaches, so it was probably unavoidable that the coalescent model would also be applied to species delimitation. The idea behind the relevant software tools such as the currently very popular BPP (disclosure: I have never used it) is that the information from multiple loci can be used to figure out how many species there are among the samples, under the assumption that samples belonging to the same species should have a history of reticulation but samples belonging to different species should have a history of (permanent) lineage divergence.

That sounds logical, but the aforementioned paper seems to hit this idea under the waterline: as the title suggests, the authors conclude that species delimitation under the coalescent resolves population structure, not species limits.

Frankly, although the method has been extremely popular lately, there has also been a lot of scepticism in the community. After all, its application has produced rather one-sided results, nearly always splitting species into several smaller species. I have heard a talk that amounted to a scathing criticism of the approach, arguing that genetic isolation of a small population for less than 200 years would be enough to make it show up as a separate "species" under the coalescent, surely a ridiculous outcome.

Consequently, the present paper fits my thinking on the issue; I, personally, would rather use clustering approaches to search for gaps in variation. But that being said, the way the authors addressed the issue still seems a bit odd to me and leaves me wondering how far their particular argument will carry.

The thing is, the study does not involve any empirical data, it is entirely based on simulations. The authors used a model under which at first only populations split and then some of them may turn into separate species after varying lag times; although there does not appear to be an explicit process in the model I guess the assumption is that it needs a bit of time to accumulate enough differences that a population cannot reunite with its sister population even if they get back into contact with each other. They then simulated species lineages under that model, and then gene trees in those species lineages, and then sequence matrices for those gene trees. And then they analysed the sequence matrices with the coalescent-based species delimitation approach trying to get the original species back.

Surprise, surprise, the coalescent species delimitation approach recovered the population splits, not the species splits. But what has this really shown? As far as I can tell, it has shown that an approach using a model counting all population splits immediately as species splits will not produce the results expected under a model not counting all population splits immediately as species splits.

Maybe I am missing something, but that is exactly what I would have expected before complex simulations on supercomputers had been conducted. If I simulate bicycle rides under a model that assumes I cycle to work at 20 km/h and then try to fit the results back to a model that assumes I cycle to work at 100 km/h I will also likely find that there is poor fit, right? But that does not tell me anything about how fast I really cycle to work, or in other words, anything about which of the two models is a better fit to reality.

Consequently I have to admit that arguments on the lines of "this real-life population that is clearly not a separate species but has merely been isolated for 200 years comes out as a new species under the coalescent approach" seem to be more impressive.

Some very, very basic notes on paper writing

The following are just a few notes on manuscript or student report writing for my area of science, which I would circumscribe as plant systematics, biogeography and evolutionary biology. I will probably at some point use this or a revised version for other purposes, but thought it might be interesting to blog about.

As should be well known, the typical research paper (and a student report mirrored after it) in my area has, in this order, a title, author names and contact info, an abstract, key words, introduction, materials and methods, results, discussion, optionally conclusions (or they may be part of the discussion), acknowledgements, reference list, figure legends, tables, and potentially appendices or supplementary data. I will only deal with some of these for now. The main text, i.e. without reference list, should probably not be longer than c. 5,000 words, and the shorter the better.

Abstract

The abstract should summarise all the other sections in really abbreviated form: what is the paper about, what main methods were used, what are the main results, and what do they mean. Do not cite references in the abstract, and do not provide taxonomic authorities after plant names. They are provided on the first mention (and only on the first mention) of a name in the main text.

Introduction

This section provides background information, describes the question or problem, and ends with aims of the study. Ideally start with general, well-established, and unproblematic claims ("biodiversity loss is accelerating", "genomic data have become increasingly available for use in phylogenetic studies", etc.) and move relatively quickly to the problem ("guidance is needed to prioritise conservation planning", "but analysis of the large amounts of data produced by high-throughput sequencing is computationally challenging"). Do not begin with your study group, unless the paper is a purely taxonomic or phylogenetic one, as this will not draw in as many readers; the introduction of the study group should come after the general question has been established.

Obviously the introduction needs to be full of references, and all but the most widely accepted statements should be followed by at least one of them.

The aims should follow logically from the questions or problems and need to tie in logically with the methods, results and discussion. They can be formulated as hypotheses or questions, but should not be too vague. Think "we will test if patterns agree with those postulated by Smith (1980)" instead of "we want to explore the patterns".

Methods

Be as concise as you can. Cite software, tests and methods, but not the most basic ones; PCR or t-tests, for example, can be considered sufficiently established. Start with the materials (sampling strategy etc.), then work logically through the lab and analysis pipeline.

Results

This section presents the results and nothing more. Any sentence that interprets the results or explains them does not belong here but into the discussion. References do not belong here. Explanation of how something was done does not belong here but into the methods.

On the other hand, all observations need to be stated explicitly in the main text of the results section, with a reference to the figure or table where they are presented. The figure legend itself should, in turn, be very concise and merely provide enough information to understand the figure, but it should not restate what the reader can see in the figure just above said legend anyway. For example, the figure legend might say "A, map of Australia showing endemism hotspots", but something like "hotspots are found in the southwest and southeast" is superfluous here and goes into the main text: "endemism hotspots are found in the southwest and southeast (Fig. 2A)".

Discussion

Perhaps the hardest part to write, it explains what the results mean and how they fit into the wider context. It may also end on suggestions for further study. The main problem for beginners is to avoid repeating what was already said in the introduction and results sections.

The discussion should again have lots of references - not because we always need to cite lots of papers per se, but because any paragraph in the discussion that does not have at least one reference can be considered under suspicion of either belonging into the results section or being mere padding.

Acknowledgements

Collaborators, funding sources, peer reviewers. For student reports, one would expect the supervisor(s) to be mentioned. It is not clear to me why many people feel the need to initialise the names of those who they are thanking, as writing them out makes it easier to identify them, especially if they have common family names.

Figures

I haven't really made a tally, but the typical article would probably have between two and six figures, after that it becomes excessive.

Journals in my area expect the manuscript text and figures to be uploaded as separate files, and they expect high quality file formats such as EPS for vector graphics and TIFs with lossless compression for bitmaps.

For exchanging a manuscript draft between co-authors, or a student report draft between student and supervisor, it is, however, probably best to insert figures into the manuscript file, because then your collaborator has less files to handle and to print. I would suggest the following approach:

Have a separate section for the figure legends after the references. This is as it should be for journal submission.

Produce EPS (vector) or JPGs (bitmap) of the figures to save on file size and insert each of them into the text directly above the relevant figure legend. Although Word allows for them, I would very strongly advise against using convoluted text boxes-inside-object boxes-inside-object boxes. A student report I once had to reformat froze my computer for several minutes when I tried to resize one of its "figures". Ultimately I had to export the page as a PDF and then export the PDF from Inkscape into yet another format, whereupon I reinserted the figure into the Word document. A journal would, of course, not accept anything like that anyway.

Select the wrapping option "in line with text". This will treat the figure like a character, meaning that it will remain anchored to its position relative to the text no matter what you do upwards of its position. If you use other wrapping options such as "on top of the text" the figures will float around freely, and changing line spacing or font size, or deleting paragraphs, will mess everything up to no end. I once dealt with a student report where three figures ended up on top of each other!

Do not use text boxes for the figure legends, or for tables, for that matter. Really, why would you? They can be normal text, just like the rest of the manuscript. In fact I have yet to see a use case for Word's text boxes in my line of work (PowerPoint is a different matter).

Language

There is no reason to use words like "whilst" where a simple "while" will do.

Often sentences can be simplified greatly; some people seem to have a penchant for writing something on the lines of "for pollination, it has been demonstrated that hummingbirds are more efficient", but the same could be said as "hummingbirds are more efficient pollinators" - saved us six words! Similarly, "in the literature it is documented that the sky is blue (Smith, 1980)" can be reduced to "the sky is blue (Smith, 1980)". And yes, I have seen sentences like these, particularly as a reviewer.

Small stuff

Do not use double spacers at the end of a sentence.

Do not have spacers at the end of a paragraph.

There needs to be a spacer between any measurement and its unit (5 km, 5 h), with the exception of temperatures (5ºC) and angles (5º).

This might seem a bit OCD, but believe me, you do not have to make some poor copy editor's life harder than it is.

Promiscuity

Recently I participated in an interesting discussion on the internet. The main topic was how some people reject scientific evidence if it contradicts their religious or ideological commitments, but the example was the nexus of evolutionary biology, male and female reproductive strategies, and differences between men and women.

It seems rather self-evident that males of nearly every species can potentially, if they are lucky and pursue the "right" strategy to achieve that end, have many more children than females. That is, after all, how female is defined in biology: it is the sex that makes the greater investment in offspring, usually at a minimum by producing a few large, immobile gametes, while the male is defined as the sex that makes the lower investment into each individual potential descendant, usually at a minimum by producing many small, mobile gametes. On top of that many species have layered additional female investment into the developing offspring, be it by giving live birth (or its botanical counterpart of producing seeds instead of spores), producing milk, or providing paternal care.

It is at this stage that the situation can, rarely, be flipped, e.g. by male sea-horses taking over the pregnancy, or male ratites raising the young; or paternal care can be shared by the sexes. But for most species, the female is the bottleneck, so to speak: How many offspring a female and a male can have is capped by the female's fertility.

It follows logically that a male can increase its number of offspring by being promiscuous, while a female cannot. The conclusion for reproductive strategies is that males in your modal species should evolve to be non-discriminating with regard to sexual encounters, and to maximise the number of partners. Females, on the other hand, do not get anything out of such behaviour. (Unless other considerations come into play, such as earning money with prostitution, or using casual sex as social glue, as it said the bonobos do.)

Whether, for example, human men are more interested in having many partners or more willing to cheat than women is a testable hypothesis. But the answer to that question is not really what I want to dwell on.

What interested me was that a lot of people who argue from reproductive strategies as discussed above write things on the lines of "men cheat more than women" or "men are more promiscuous than women". Also quite interestingly, rarely somebody will pop up who argues the opposite, claiming that "women cheat more than men". Honestly I do not understand the logic for that latter claim, as it does not even have the advantage of making sense from an evolutionary biology perspective; the idea that it is based entirely on misogyny is at least not easily dismissed.

But really for present purposes both claims can be treated as equivalent: I think both of them are, equally, mathematically impossible.

Yes, perhaps it can be shown that men are wired to seek more partners; maybe that is even biological as opposed to cultural. But that does not mean that they will be successful at having more partners, and that is unfortunately what being promiscuous means. Wishing is not doing.

Assume equal numbers of men and women, and disregard homosexual pairings, as neither of these factors are what those who claim "[gender] cheats more than [other gender]" are concerned with. Make a row of female circles on the left and a row of male circles on the right. Now draw lines between female and male circles to indicate pairings.

You can end up with very different network structures, of course. You could have three quarters of all men unpaired, while a quarter of them is paired with four women each, a harem scenario. You could first have each man paired with one woman, and very women also paired with lots of men, a prostitution / men cheat a lot scenario.

But it is simply impossible to have more average promiscuity on the left than on the right, or vice versa, because obviously all connections start on the left and end on the right, meaning that promiscuity is in all cases = number of people of that gender / connections, and we assumed equal numbers of men and women.

Arguments could perhaps be made about the median, but that is not what people intuitively mean or understand when somebody says, for example, "women cheat more than men". Claims like those just don't make any sense, and one doesn't even have to collect evidence on that. They fail right out of the gate, on basic logic.