The Devil’s dictionary, April 20, 2018

more entries in the Devil’s Dictionary: today including altruism, heterochrony, etc.

See the complete Devil’s Dictionary of Scientific Words and Phrases here.

3707_001

all entries in the Devil’s Dictionary copyright 2017 by Russ Hodge

age  is a short suffix that can be added to most nouns and a few other speciages of wordages if you can get them to hold still long enough to attach it. Its original usage stemmed from attaching the word “itch” to something that caused one. “I wouldn’t give you five cents for that beddage (bed-itch),” someone might say, implying that a mattress was full of lice. Other spellings were incorporated early on: “radish” comes from “red-itch,” as some who ate the vegetable developed a rash. Later British noblemen began to add “-age” to words under the mistaken impression it derived from a similar French suffix (“personne” becomes “personnage”), and that using it would suggest they spoke French, which would people think they were more intelligent, higher-class, and cooler than they actually were. They used the suffix to make simple things seem more complex and sophisticated than they actually were. A “dosage” was something a physician gave you; a “dose” was something acquired in a less respectable social setting, and the reason for your visit to the doctor in the first place. A nobleman referred to his social equals as his “peerage”, aiming to imply that they deserved respect; the unintentional irony was that more literally, you were saying he was “lousy” (full of lice). This use of “-age” to make things sound more intelligent or technical has persisted to modern times. “Usage” is often favored over “use”, although they mean the same thing. And you’d never listen to a relative go on and on about the amount he pays for gas, which is nothing more than griping and his own dumb fault for buying the car; “mileage” sounds more technical and scientific, and can start a discussion that lasts for hours.

altruism  a disputed term used by some psychologists to describe a temporary, dissociative cognitive state marked by mental confusion and unnatural behavior. The most distinctive symptom is that a person suffering from altruism places the well-being of others above his own, even when this involves risky and even self-destructive behavior. This extends to individuals beyond his or her own children in what has sometimes been described as “an overgeneralization of the mothering instinct.”

Altruism seems so contradictory to evolutionary principles that some refuse to believe it exists and try to explain every altruistic act as ultimately selfish. The problem troubled Darwin to the point that he put off publishing the theory of evolution for more than two decades, spending more than half of that time in a painstaking study of barnacles. This aquatic creature is commonly used as an animal model of human altruism because in some sub-species, males have given up their bodies altogether in service of females, now existing as little more than a sac of sperm, a sort of parasite inside the female body. Darwin finally resolved the conflict by realizing that short-term altruistic behavior might have a function like bird plumage, by attracting potential mates. It might fool someone into thinking you were “nice”, at least long enough to invite home for a few rounds of reproductive exercise. Most bouts of altruism wear off quickly, within a few hours, but the original performance might have been so impressive it could years for a mate to realize it was a temporary aberration, and the victim is normally just as selfish as everyone else.

Diagnosis is tricky and altruism can only be definitively detected through EEG recordings and a brain scan. These measurements reveal a depressed activity in areas of the brain related to basic instincts of self-preservation and higher cognitive functions, akin to the brain’s response to canniboids. The longest duration for a uninterrupted altruistic state recorded in medical history is four hours, although the patient was sedated for most of that time.

heterochrony  the inability toremember whether to set your clock ahead or back at the beginning and end of Daylight Savings’ Time, and then to draw the proper conclusion about whether you have gained or lost an hour. As for what happens at the International Date Line… Forget it. Severe cases of heterochrony are often accompanied by a conspiracy theory mentality which holds that the hour isn’t really gone you lose an hour no matter which way you turn the clock, the result of a governmental conspiracy to steal an hour from citizens twice a year, during which it has unique access to your bank account and has an hour to invest your savings in highly speculative stocks, or work the slots at an on-line casino. There is little risk because it will just add any losses to the amount due in calculating your income tax. You never notice that anything has happened because the extra hour never officially existed – they keep shuffling it back and forth across time zones – and although your money is gone, this does not appear on your bank balance. And why should it? There was never actually any physical money in the account anyway. They keep it stored in ATMs.

A woman with the condition is called a heterochrone; the male form is heterochronus, their offspring are labeled heterochromognomes. Compare with homochrony, which has nothing to do with Daylight Savings Time.

homochrony  the ability to march or clap, although not necessarily simultaneously, at a regular pace coordinated with the rhythm of any marching or clapping going on around you. Animals either do this instinctively or don’t care; in humans early training helps. The technical term for people who never acquire this skill (famous case: Ronald Reagan) is “ain’t got no rhythm.” Those who do got rhythm can refine it to the point of being able to march in formation while twirling a baton or playing a musical instrument, despite wearing a bizarre band costume that resembles the attire of the British colonial forces that occupied India.

to proportionate (verb)  an aggressive social behavior in which a person proactively volunteers to cut the pie, or the chicken, or divide the loot, in a thinly disguised move to get the most. After things have been divvied up, the distribution is said to be “proportionate” (adjective) if the portions people receive correspond to the amounts they deserve, calculated through a complex formula that takes a person’s body mass index into account and variables such as whether your spouse feels that your BMI falls into an acceptable range, whether he or she is presently at the table, and the H (holiday) factor, where the normal physiological regulators of eating are repressed. If a proportionatee disagrees with the amount he has been proportioned, he may petition a civil court, at which point he has the opportunity to present evidence that his piece of pie was too small. The court may order the plaintiff and defendant to enter a binding process to decide on “reproportionation,” to whose terms both parties must agree. If they are unable to come to terms, the case is heard again and decided by the judge.

book lice  a parasite created through genetic engineering techniques by introducing termite genes into head lice. Originally developed for their potential as a form of organic recycling, librarians got their hands on the bugs and began cultivating them in S1 laboratories in the library basement. Staff harvest the colonies for their eggs, which are spotted onto the pages of books before they are loaned out. The eggs are timed to hatch precisely one day after the date due, at which point the lice crawl out of the book and take up residence in nearby volumes on the patron’s shelf or any available textile, which is why you should never read a library book in bed and should always return it on time. The eggs are highly sensitive to changes in the environment of the book; improper handling, such as dog-earring a page, often triggers early hatching. Book lice are to library patrons what the dye packs they hide in currency are to would-be bank robbers.

host  has two distinct meanings in science. The first is a deragatory term by which unicellular organisms refer to multicellular life. For bacteria, “host” has about the connotation of a motel whose rooms have no bath, no cable service, and whose swimming pool is exactly the size of a Jeep, namely one that missed the exit ramp on the Interstate, flew over the guardrail, and plopped into the pool, where it was such a tight fit that it could no longer be extracted. A pathogen goes off on a trip for a while and takes copious notes, so that when it comes back it can compare its holiday experience with those of the neighbors. Bacteria can’t access the Internet, so they distribute their reports biochemically, sometimes at the level of genes. Over time individual human bodies are ranked in terms of comfort and the level of services they provide. Very few people are awarded a five-star rating, and when it happens the pleasure is short-lived. They become vacation hotspots that are overrun by all sorts of pathogens, inevitably killing the host, but by that time a trendier new place has usually been found.

The second usage of hostin scientific contexts is positive: as a term of respect that one scientist may bestow on another after being invited to give a talk at the colleague’s institute. “Host” is reserved for someone who covers all of your travel expenses, naturally first-class, takes the visitor to excellent restaurants, where the prices on the wine list are explicitly ignored, and puts you up in a four-room suite at a hotel with all the amenities, such as an all-night bar well stocked with attractive, lonely conversation partners. Upon request a host will assign you a bodyguard to escort you to the bar, stay discretely on hand to jump into any fights that may arise, and then get you get back to your room in one piece, unless you indicate otherwise using a secret sign agreed upon in advance, possibly but not necessarily indicating that you have managed to hook up in the bar. If the hosting scientist fails to meet any one of these criteria, you return home and insert a reference to the trip whenever possible in casual conversations, and write an exhaustive account of the visit on websites such as LinkedIn, but conspicuosly neglecting to refer to your colleague as the host. Being at least as smart as pathogens, other scientists get the idea, and will make up wild excuses to avoid having to give talks at institutes rated with four stars or below.

hatch  As a verb, hatch refers to the process by which an organism emerges from the receptacle in which it has undergone the stages of embryogenesis, whether an egg or a womb, often freeing itself by pecking an opening with its beak. So birds hatch from eggs and children hatch from the womb, unless the child is an amphibian or a reptile.

As a noun, hatch refers to a flap-like tissue that covers the throat which remains closed until it is stimulated by a liquid of high alcoholic content. This triggers a reflex by a hinge-like muscle at the back of the flap, causing it to open and permitting the alcohol to go “down the hatch”. From there it is routed to special cavities throughout the body that are dedicated to the processing of alcohol. There are several of these tubular structures, located in regions such as in the legs, where gave rise to the expression, “He has a hollow leg.” (The technical term is overflow lumen.) When alcohol enters such a lumen, it causes a sensation that the drinker reports as, “That really hit the spot.”

hindgut  a region of the intestine which lies below the hindbrain, when the body is in an upright position, and is connected to it via a large bundle of nerves that bypass the spine. This conduit permits the gut to monitor brain activity and take over some of its functions, such as communication, in an emegency. When a person is incapacitated, for example through the excessive consumption of alcohol, or decapitated entirely, the hindgut steps in and sends unequivocal signals of distress to those nearby. It has two modes of doing so – generally trying one and waiting for a response before trying the other. If neither on its own provokes other people in the bar to take caregiving measures – such as calling an Ueber driver – the hindgut activates both signaling systems simultaneously.

In type 1 signaling, the hindgut jerks swiftly upwards and delivers a focused “punch” to the stomach, which forces its contents upwards in the form of projectile vomiting. In type 2 it presses downwards, clenching the lower intestines in a vise-like grip that forces any pockets of noxious gas to seek the nearest exit, generally accompanied by a loud acoustic signal. Such noxious gases are usually plentiful because the body naturally produces them as it metabolizes fermented substances.

flocculate  the process by which a floc is produced from a microfloc. What happens before that, no one knows, but microflocs can’t just arise from nothing, so it is reasonable to infer the existence of nanoflocs. Anyone who cares about what comprises nanoflocs – there’s something wrong with you.

ooopossum  the oocyte of a possum.

If you liked the Devil’s Dictionary, you’ll probably also enjoy:

Searching for Oslo: a non-hypothesis-driven approach

On the publication of “Remote sensing” by the magazine Occulto

 

Advertisements

A dialog on ghosts and models in science

This is the first of several pieces in response to questions I have received about my recent lengthy article (too lengthy!) on “Ghosts, models and meaning: rethinking the role of communication in science.” Read the full article here.

Can you give me a succinct definition of the “ghosts” you’re talking about?

There are a lot of contexts in which science communication somehow fails because an audience doesn’t get the point or understand a message the way it was intended. The naïve view of this is that scientists just know a lot more about a specialized topic than people from other fields or the public. That happens, but it’s rarely the biggest issue in communication – and it doesn’t explain why people have problems writing for experts in their own field.

When I began teaching scientists to write I came across a lot of content-related breakdowns that were hard to understand. This got so frustrating that I finally decided I had to systematically analyze the problems I was seeing. That took about four years, and “ghosts” emerged as one of the most frequent and important issues.

Ghosts originate from many things: concepts, frameworks, logical sequences, other patterns of linking ideas, theories, images and so on. What unifies them is that the author has something in mind as he composes a message, and it is essential to understanding what he means – but he never directly articulates it in the message itself. He may not even be aware of it. Since it’s nowhere to be found in the message, it’s invisible; if the reader doesn’t sense its presence, or can’t easily recover it, it disrupts his understanding of what the author means.

This is true of all kinds of communication, but the natural sciences have some special ways of assigning meaning to things that really need to be taken into account when you’re planning a message or trying to interpret one. If you don’t, you’re setting yourself up for misunderstandings.

 

You mention models again and again – why are they so central to these misunderstandings?

Among the most significant and disruptive ghosts in science are various models that are used in formulating a question or hypothesis and interpreting the results. Most studies engage many types and levels of models. Scientists obviously recognize this; as Theodore Dobzhansky said, “Nothing in biology makes sense except in the light of evolution.” But there is a big difference between acknowledging this and demonstrating how something like evolutionary theory reaches into very basic practices, such as how scientists name molecules. And there’s a big invisible ghost behind Dobzhansky’s statement – something he doesn’t explicitly state but is essential to understanding what he means. Evolution itself is based on even more fundamental principles of science, so if you’re talking about the theory, you’re also talking about them. In fact, most “debates” over evolution are actually arguments about even bigger things, and if you don’t confront that level of the disagreement, it doesn’t even really make sense to discuss whether species change or go extinct or the other topics that these discussions always get mired down in.

 

What are those specific ghosts?

I think there are two, and they are so basic that they distinguish science from other ways of thinking about things and assigning them meaning. I call the first one the principle of local interactions: if you claim that something directly causes another thing, you either prove or assume that the cause and effect come in contact with each other in time and space, or are linked by steps such as a transfer of energy that follow this rule. So to make a scientific claim that a child inherits traits from its parents, you have to find some direct mechanism linking them, such as the DNA in their cells. It is directly passed to children from the reproductive cells of their parents, and it’s the blueprint that creates bodies through its transcription into RNAs and their translation into proteins.

The second principle applies this type of causality to entities as complex as organisms or entire ecospheres and declares that the state of a system arises from its previous state through a rule-governed process. And it will generate future states through the same rules. You may not know what they are, but you assume they are there, and a lot of scientific work is devoted to creating models that will expose them. If you follow this principle you can observe what is going on in a system right now and project it far into the past and deduce its previous states. This is the source of the Big Bang theory in astrophysics; it’s the basis of geology, and when Darwin applied it to life he got evolution. Extending the principle into the future is the basis of the experimental method used to determine whether your model of a system is accurate enough to work with – if something in an experiment violates predictions made by the model, you have to revise it.

Anything that violates the principle of local interactions would be considered non-scientific. That’s the case for extrasensory perception – until you can demonstrate that some energy passes from one person’s mind into another’s, you can’t make a scientific claim for its existence, so you have to look closely into whatever model of causality led you to claim it might exist. And the second principle implies that there are no discontinuities – you can’t create something from nothing. Miracles and the fundamentalist account of creation violate both principles.

If you can’t agree on these two things, it makes very little sense to discuss details of evolution that derive from them, because differences in your very basic assumptions will make it impossible to reach any sensible common ground – or even define some of the terms you’re talking about. So these principles are ghosts in “debates” on this topic, and they are the things you need to debate, providing you can do so fairly, with intellectual honesty and integrity.

 

You came up with this concept of “ghosts” while working on texts by students and other scientists. Why are they a particular problem for students?

Active researchers are deeply engaged with their models; most projects take place in a fairly exact dialog with models you are either trying to elaborate on by adding details, or extend to new systems, or refute through new evidence. This makes models very dynamic, and there’s no single reference on the Internet or wherever where you can go and find them. In biology virtually every topic gets reviewed every year or two, which is an expert’s attempt to summarize the most recent findings in a field to keep people in a field more or less on the same page. That’s the group that a lot of papers and talks are addressed to, at least most scientists think that way – and they assume the readers will have more or less the same concepts, models and frameworks in mind. Anything that is widely shared, people often fail to say – they think they don’t need to. And it’s impossible to lay out all the assumptions and frameworks that underlie a paper within it – you can’t define every single term, for example. So these become ghosts that aren’t explicitly mentioned but lie behind the meaning of every paper. The two really huge basic principles I mentioned above are rarely, rarely described in papers.

And even the details of the models more directly addressed by a piece of work – the physical structure of the components of signaling pathways, or all the events within a developmental process – aren’t mentioned very often. Those models are embedded in higher-level models, and the relationships in this hierarchy are not only hard to see – there’s no single way of explaining them. Scientists sometimes work these things out fairly intuitively as they extend the meaning of a specific set of results to other situations and higher levels of organization.

Now imagine a science student who is absorbing tons of information from papers like these. As he reads he’s grappling with understanding a lot of new material, but he’s also actively building a cognitive structure in his head – I call it the “inner laboratory, or cognitive laboratory.” It consists of a huge architecture in which concepts are linked together in a certain structure. The degree to which he understands a new piece of science depends on how that structure is put together, and where he plugs in new information. If the text he’s reading doesn’t explicitly tell him how to do this, there will be a lot of misinterpretations.

How can his professor or the head of his lab tell whether a scientist under his supervision is assembling this architecture in a reasonable way? You catch glimpses of part of it in the way someone designs an experiment, but I think the only method that gives you a very thorough view of it is to have the young scientist write. That process forces him to make the way he links ideas explicit and put them down in a way you can analyse each step. In writing – or other forms of representation, such as drawing images or making concept maps – you articulate a train of thought that someone else can follow, providing a means of interrogating each step. Most texts are pretty revealing about that architecture; if you read them closely you can see gaps, wrong turns, logical errors, and all kinds of links between ideas that a reader can examine very carefully.

The problem is that in most education systems in continental Europe, in which most of the scientists I deal with were educated, writing is not part of the curriculum. Whatever training they have is done in all sorts of ways, and the teaching is usually not content-based. Instructors use all kinds of exercises on general topics, but that learning doesn’t transfer well to real practice. Why not? Because when you write about a general theme, your knowledge is usually arranged very similarly to that of the teacher’s and any general audience. In your specialized field, on the other hand, your knowledge is likely to be very differently arranged, and that’s where the ghosts start to wreak real havoc on communication.

 

So ghosts aren’t just things that scientists leave out of texts – they’re also phenomena that arise from the reader or audience…?

Absolutely – they arise from differences in the way a speaker and listener or a writer and reader have their knowledge organized. That can happen in any kind of communication, but in science it’s actually possible to pin ghosts down fairly precisely. In political discussions or other types of debates there aren’t really formal rules about the types of arguments that are allowed… But if you know how meaning in science is established, you can point to a specific connection in a text or image and say, “To understand what the scientist means, you have to know this or this other thing.” Again, since neither of you can directly see what’s in the other’s head, a reader may not guess that some of the meaning comes from very high levels of assumptions, or a way of organizing information that you’re not being told. And some have been digested so thoroughly by scientists that they’re no longer really aware that they are there.

Some of the most interesting ghosts appear when you try use someone’s description of a structure or process to draw a scheme or diagram. I recently had to draw an image of how a few molecules bind to DNA because we needed an illustration for a paper. I thought I had it clear in my mind, but I ended up drawing it five times – each version incorporating some new piece of information the scientist told me – before I got it the way she wanted it. You learn an incredible amount that way.

A scientific text is often based on an image of a component or process that a scientist has in his mind. He’s trying to get a point across, and to understand what he means you have to see it the way he sees it – but if he leaves anything out, it’s easy to completely miss the logic. It’s like trying to follow someone’s directions… That works best if the person who’s giving the instructions can “see the route” the way it will appear to you, maybe driving it one time to look for the least ambiguous landmarks, or taking public transportation and watching exactly what signs are the most visible. And thinking it through with the idea, “Now where could this go wrong?”

 

Another thing you refer to is concept maps – you include several examples in the article. How do they fit in?

Concept mapping is a system invented by a great educator named Joe Novak; it gives you a visual method to describe very complex architectures of information. It’s extremely useful in communication, teaching, and analyzing communication problems. One reason it’s so important is that our minds deal with incredibly complex concepts that are linked together in many ways. Think of trying to play a game of chess without a board – that’s incredibly difficult, but a chess set is a fairly simple system compared to most of those that science deals with. There’s really no way to keep whole systems in your head at the same time. Making a map gives you a chance to see the whole and manipulate it in ways that would be impossible just by thinking about it.

But the real genius of this system appears in communication and its most precise form – education – where a teacher ought to understand what he is really trying to communicate, and how it’s likely to be understood by the students or audience. In most cases you’re hoping to do more than just “transmit” a list of single facts; you’re trying to get across a coherent little network of related ideas, linked in specific ways. If you do that successfully, the audience will leave with a pattern they can reproduce later. It might be a story, a sequence of events, or a metaphor – the main thing is, they have seen how the pieces are related to each other.

A great way to do this is to make a map of the story you’re trying to tell, and then make your best guess about how this information is arranged in the heads of your target audience. What can you realistically expect them to know, and what information and links are likely to be new? If you see the pattern you’re trying to communicate very clearly, and make a reasonable guess about how some type of knowledge you can relate it to is arranged in your audience’s head, you know what you have to change to get them to see things the way you’re hoping. In schools they’re teaching kids to make concept maps early on. Then before a lesson about something like the solar system, the teacher has the kids draw a map of what they think about the sun, moon, planets, and so on. After the lesson the kids make a new map – comparing the two tells you what they’ve really learned.

 

In your article you point out ghosts that come from schemes like sequences of events or tables…

A lot of scientific models consist of sequences of interactions between the components of a system. Those start somewhere and involve steps arranged in a particular order, and it’s important for the reader to have a view of the steps and that order in his mind. You’d be surprised how often scientists describe these processes in some bizarre order that doesn’t go from A to K, but starts at G, goes to H and I, then goes back to G and works backward to F, E, and D… Again, if you are already familiar with the sequence or pathway this is no problem. But if you don’t, you’re probably expecting the reader to try to assemble the process in some reasonable order. That may be possible through a careful reading of the text, but it takes far more “processing time” than a reader would need if the whole sequence were simply laid out in order in the first place.

Tables are interesting because a lot of experiments are designed with a structure that’s pretty much inherently that of a table. Say you have two experimental systems plus a control, and you apply two procedures to all of them. To make a claim about the results, you have to march through all these cases – basically a table that’s 3×2 or 2×3. Here again, you’d be surprised how many scientists’ descriptions skip over some of the cells of the table, mostly because the results aren’t very informative. Or they tell you, “Procedure A caused a 5-fold increase over Procedure B,” without telling you what happened in the control.

Both of these effects are due to a scientist’s failure to recognize the structure of the information he has in his head and is trying to present… Then he fails to present that structure in the text in a way that’s easy for the reader to rebuild in his own head.

 

You’ve said that ghosts are one component of a larger model you’re working on that reformulates the relationship between science and communication… What else is there?

A lot of the other points can be captured through an exploration of what I call this “inner” or “cognitive” laboratory of science. The really good scientists I know have a very clear understanding of their own thinking. They know the assumptions that have gone into the models they are using, and are aware of the limitations, where there are gaps and so on. That type of clarity usually translates into good communication, no matter what the audience.

One thing I found during this project that was very surprising was the extent to which writing and communication for all kinds of audiences was connected, and how addressing very diverse audiences could clarify thinking in a way that improved a scientist’s research. When you find a scientist struggling with clarity in a text, it usually means one of two things. Either a topic is not clear in his head at that moment, or it’s not clear in anybody’s head at this moment in science… That second case is very interesting because it means you can find interesting questions just through a very careful reading of a text, realizing that it’s asking you to build a certain structure of ideas. If you have difficulty, that means something. One of the basic strategies I used in working these things out was that problems are meaningful – they’re trying to tell you something about how good science communication works, or how scientific thinking works… usually both.

Speaking to a general public with really no specialized knowledge of a field can be a truly profound exercise for a scientist. It makes him interrogate his own knowledge in alternative ways. He has to come to a much more basic understanding of the patterns in his inner laboratory and apply different metaphors, trying to map that knowledge onto someone else’s patterns. Well, the cognitive laboratory is already metaphorical, based on concepts rather than real objects, and applying new patterns or metaphors to what’s in there is extremely interesting. It can suggest questions you’ve never thought of before. This means that tools that have been developed by linguists and communicators can be used as tools to crack open scientific models.

I’ve actually done this – used those tools to expose an assumption about evolution that everyone was making but wasn’t usually aware of. The assumption had never been tested, so my friend Miguel Andrade decided to take it on as a project, and put a postdoc on it. The results were really interesting, showing that there were a lot of cases where the assumption didn’t hold – and we got a published, peer-reviewed paper out of it. That was three years ago, and in the meantime I’ve been involved in a number of similar projects that have had a similar outcome. A communicator who pursues questions about meaning and language has a different set of tools to understand how ideas are linked in scientific models. You’re freer to apply slightly different metaphors and patterns to ideas; you may be more rigorous in perceiving assumptions; metaphors and other tropes help you see cases in which people are reasoning by analogy rather than strictly adhering to the system at hand.

So these ideas aren’t just a way to help people plan and communication better – although they certainly help in those tasks. In fact they are much more fundamental in scientific thinking. Understanding these relationships between communication and science is a pathway to doing better research, through a better understanding of its cognitive side. I’ve noticed recently, for example, a lot of cases where the way people are thinking of complicated processes is drifting away from the language they use to describe them. The language is conservative and it may be hard to adjust. But that will be essential as the models these fields are using move forward and become so complex that our minds – and our language – may not be truly able to capture them.

 

 

 

The Devil’s dictionary, March 22, 2018

Finally more entries in the Devil’s Dictionary! Today’s words:  fixing, biomass, drift, and skeletal muscle

See the complete Devil’s Dictionary of Scientific Words and Phrases here.

3707_001

all entries in the Devil’s Dictionary copyright 2018 by Russ Hodge

fixing  In basic research this term generally refers to chemical methods of preparing a living creature or one of its parts, such as a cell or a tissue, but also a complete organism such as a group leader, so that all of its biological processes are immobilized at the moment of fixation. This is useful if you want to examine the mechanisms that underlie a behavior you do not understand, such as the organism’s refusal to give you feedback on your latest paper. It has the slight disadvantage of killing the object of research. In clinical science, “fixing” usually refers to methods of removing the reproductive organs of an animal so that it won’t engage in uncontrolled, promiscuous acts that would lead to lots of offspring. Given a choice between the experimental and clinical types, most organisms would probably prefer the first.

biomass  is used in two ways: 1) the “weight of life.” If you weigh a living organism such as a human being directly before and after its sacrifice, the biomass is the difference. The biomass is just that part of an organism’s weight contained in the Life Force. Some distinguish it from the soul, whose weight must then be subtracted from the Life Force total. If the death produces a ghost, its weight must be subtracted as well. This leaves a biomass that is usually very small, about .000001 grams, although some scientists maintain that this represents the weight of the last breath instead of the Life Force. Others believe that the Life Force and the last breath are the same thing, particularly if you have been eating garlic. If the weight after death is heavier than before, then you’ve waited too long to perform the measurement; the extra weight comes from bacteria and other decomposers which have settled into the organism for the feast and begun to reproduce. People who don’t believe in a Life Force, a soul, or a ghost are not only sort of boring, but they have a more boring definition of biomass: 2) the weight of every living thing in an environment, measured after you’ve stacked it in a big pile.

drift  a situation in which the younger generations of a species pack up and move away from the herd, taking their genes along with them. At some point youngsters get fed up with parental control, stuff a bunch of clothes in a backpack, and head off aimlessly on a railway pass, leaving its parents to wonder whether they have taken along a toothbrush. The young generations keep traveling until they have spent all their money, find an ashram that suits their nature, or both. When they reproduce their children go through the cycle all over again, leaving the ashram for other parts.

skeletal muscle  long fibers made of fused muscle cells that connect various regions of the brain to different points on the skeleton, turning the body into a sort of marionette and creating the illusion that we have conscious control over it, although some people obviously don’t, at least not their mouths. Skeletal muscle is the foundation of voluntary movement by animals. Before it evolved, animal movement was strictly involuntary – if a pet or child were in the way, you had to pick it up, throw or kick it to make it move. The arrival of skeletal muscle was highly practical because it permitted people to make the trip from the sofa to the refrigerator themselves; you no longer had to spend all your time fetching beer for them.

Skeletal muscle promoted the development of some further evolutionary adaptions while retarding others. Experts believe that it delayed the evolution of language because skeletal muscle allowed animals to use the digits of their forelimbs to point at things. Pointing served all the important functions of language that a species needed except for those that required head-butting or biting. But it also led to negative selection, because having control over your finger made it possible to poke someone else in the eye, and you could no longer blame such behavior on the absence of skeletal muscle. This often led to negative selection through the loss of the finger in question, as well as whatever functions it served in the survival and reproduction of an individual.

grey matter  another term for scientific publications.

 

If you liked the Devil’s Dictionary, you’ll probably also enjoy:

Searching for Oslo: a non-hypothesis-driven approach

On the publication of “Remote sensing” by the magazine Occulto

 

Ghosts, models and meaning in science

Rethinking the role of communication in science

by Russ Hodge, copyright 2018

Read the article here

This article is intended for all the stakeholders in the broad field of science communication: from practicing scientists at all stages of their careers to science students and teachers, journalists, communicators, and educators. It could also be of interest to linguists, cognitive psychologists, and others interested in the connection between thinking and language. I hope it will be read by those responsible for university programs across Europe, because it provides several arguments for making communications training a standard part of their curricula.

Here I bring together ideas that have been dealt with superficially in other pieces (1, 2, 3, 4) on the blog.

This is a rough draft, one of at least three more major parts to come. In it I aim to demonstrate that the relationship between science and communication is far more profound and interesting than we usually consider. The process that most of us go through when we want to communicate well is crucial to clarifying thinking, and it offers tools that could be used much more strategically in posing new scientific questions and interpreting data. To say this as boldly and plainly as possible: learning to communicate well can improve your scientific work – not only because your papers have better grammar, but because it requires a type of thinking that is extremely useful for science.

I do not say this lightly; I know how skeptically most scientists will greet it. That’s fine; I have waited a long time to write this piece because I needed to collect powerful examples to support it and put them together in a convincing way. If you are a scientist, I hope you will recognize aspects of your own thinking in this piece, and feel that it puts words to things that have become your daily habits. It may even surprise you by revealing “mechanisms” of thinking that you have never considered, yet use all the time.

It has been a long road to get here: 20 years of interacting with scientists at all levels of their careers on a daily basis, working together to find didactic approaches to a wide range of problems, and over 30 years as a teacher overall. Yet it wasn’t until a few years ago that I finally decided to confront some frustrating, content-related problems that constantly arise while helping my students and colleagues write, speak, or communicate in other ways about their work . I realized that we didn’t have a very good model to describe and hopefully understand a lot of the problems they encountered. That motivated four years of systematically analyzing these problems. I came to several conclusions:

  1. Science and communication are profoundly linked at a deeper level than we usually appreciate, which has significant implications for science education programs and the ways individuals, institutes and organisations communicate their work.
  2. The process of writing or preparing a talk is usually essential in clarifying and organising one’s own scientific thinking.
  3. This process requires a thoughtful reconsideration of the scientific models related to a project and can expose weaknesses or hidden assumptions that need to be reexamined.
  4. Every experiment represents a dialogue with models of many types and levels and the results may say something about all of them.
  5. Becoming aware of hidden connections in the structure of scientific thinking can powerfully affect our interpretation of results and generate important new questions.
  6. Communication offers an extensive set of tools which can be systematically applied to scientific problems and improve the quality of research.
  7. Scientific models are highly complex cognitive architectures that individuals construct in their minds and integrate into an “inner laboratory” where the “real science” takes place.
  8. The only way to examine these architectures is by externalizing them in writing, talks, images, or other modes of representation
  9. Effectively speaking to the public or non-specialist audiences usually requires seeing familiar systems through new patterns. Doing it well requires a process that can clean up sloppy thinking, help us approach an old theme in a new way, generate new scientific questions and suggest alternative interpretations of experimental results.

I know, the last one’s the big one.

The text starts with a short theoretical introduction. After that I apply the principles it introduces to nine case studies taken from real students’ texts, papers, images and other examples of science communication.

This model is just a beginning, but it has some powerful implications for the way we train scientists and teach them to communicate. It strongly suggests that effective training in these skills should be an integral part of a scientific education early on and continue through a student’s career. But before people start changing their curricula, scientists need to have a convincing model that shows them why it is important, and the method of teaching must be effective. I think this is a start, but it will need to be tested in many formats and teaching environments to be validated and improved.

The model I propose is not comprehensive; I will add another major section on metaphors and patterns in scientific models and a third that specifically explores how these ideas can be practically translated into teaching. I am hoping to work with teachers who are interested in learning the theory and methodology, applying it to other types of science, and becoming multipliers. I think this is the only way to achieve the long-term goal of institutionalising this type of training and ensuring that it becomes a staple of university science curricula throughout Europe.

I need and would greatly appreciate feedback from all stakeholders in this process. Please be as critical as you like; the model has to be tough enough to take it. I will consider all of your comments very carefully, report on them here, and use them to develop better versions of this text, the model it presents, and the teaching that results from it.

 

Thanks in advance,

Russ Hodge

Please contact me at  hodge@mdc-berlin.de if you would like to discuss this personally. Also if you are interested in teaching or training in these fields, in learning the methodology yourself, or would like to discuss setting up workshops or a program to implement its ideas.

Russ Hodge, March 2018

Read the article

I would like to thank all the scientists who have been such great teachers and given so generously of their time helping me over the past 20 years, the students who continue to inspire this project, the teachers who have been a continual inspiration, and my family, friends, and colleagues present and past for their support. 

I would like to particularly thank Prof. James Hartman of the University of Kansas, an extraordinary teacher, lifelong mentor and friend, for setting me on this path so many years ago and stimulating my ideas at exactly the right moments over the years;

Joseph Novak, father of Concept Mapping and one of the most brilliant educators I have ever met, who in a single week at Cold Spring Harbor completely changed my views of the goals of teaching and the methods needed to achieve them;

Jochen Wittbrodt and the COS department at the University of Heidelberg, Gareth Griffiths at the University of Oslo, and Thoralf Niendorf at the MDC for being constantly supportive and serving as the guinea pigs in this crazy endeavour.