I consider myself somewhat sympathetic to the view being put forward, but this is just lazy writing.
> How does one measure happiness? Psychologists can’t use a ruler or a microscope, so they invent an arbitrary scale.
All scales are arbitrary. We measure length in meters for no reason other than the meter is a nicely human-sized measurement. I'd maybe even argue that the definition of a scale is that it's arbitrary, a mapping of /something/ onto the number line chosen in a way that the numbers are within "human" range.
The real difference being highlighted isn't anything to do with measurement, it's just a difference in dimensions. It's very obvious how we can compare 2 things in space-time dimensions, either they happened at different times that we can map onto our time scale, or they occupy different sizes in space that we can map onto our space scale. Emotions aren't quantifiable in these dimensions, but that doesn't mean we cannot create a space in which they are.
If the author would argue that happiness isn't a "thing" in the way "this piece of paper" or "1945" is, I think that argument can be had, and has been taking place over thousands of years of philosophy. To not even raise the question, but (in my eyes) to assume the answer as obvious, is, as I said, lazy writing.
To add to your point, any psychology/sociology researcher trained in quantitative methods will immediately recognize that “happiness” is a latent variable.
Quantitative psych people are well versed in how to think about and model latent variables. They don’t go “oh shit! can’t measure happiness, I guess we’d better just make stuff up.”
I’m plenty critical of the research coming out of psych, but to pretend that the field remains naive to even the most basic principles of modeling is a bit ridiculous (and like you said, lazy)
Reproducibility in social psychology is less than 50% [1].
So yes I do think the majority of psych researchers are making stuff up (through p-hacking and other nefarious means) in order to get funding and tenure
A question the 50% figure raises is - what is the reproducibility rate for “real” science? This is difficult to estimate. Considering the dramatic improvements in cancer therapy, one might argue that cancer research is a “real” science, but there are reproducibility issues in that field as well. [https://www.nature.com/news/cancer-reproducibility-project-r...]
And the link to the replication index site connects us to an article about John Iaonnidis, who suggests that most medical research results are wrong. (The article concludes that perhaps only 27% are false discoveries.) So what is the threshold? As others have pointed out, it’s probably more about process than reproducibility, though reproducible results are certainly preferred.
I think that would depend on how much intersection there is between the sort of scientists doing non-replicable research (mostly in academia, it seems) and the sorts of scientists developing working cancer therapies (mostly in pharma?).
I don't know if arguments about "real" science are especially useful. The nature of science has changed a lot of over time and will presumably keep changing. It takes us into questions of whether fields that can't do experiments are "real" science, for example. It also assumes replicability is the only way science can't be "real" but there are some fields (e.g. COVID research!) where papers are usually replicable but that is meaningless because the methodology is unsound in other ways, i.e. you'd just be replicating their mistakes.
The biggest problems driving non-replicable research are the fact that so much "science" is now really just data analysis, and finding some spurious correlation that just about nudges over some arbitrary and very weak threshold for significance can be considered "science", even without anyone doing any kind of double check or followup. No real world experiment needs to be done at any point. And in some fields the connection to reality has been completely lost - public health is filled with papers that make predictions about the future trends in public data, and nobody ever follows up with papers that compute the correlation between the predictions and measured values. It would be easy, but they generally don't do it.
There are several high visibility papers on lack of reproducibility in drug development by Pharma, so I don't think there is a particular bias in less reproducible research. Indeed, since life sciences research in academia is almost all funded by the NIH, with grant reviews/renewals every 3-5 years, there is probably more scrutiny of academic research than commercial.
People usually underestimate how difficult it is to do experiments, especially when you want to get quantitatively consistent results. Physics experiments sound easier than human experiments, but if you really do it and be serious with the numbers, you will find even high school physics experiments are really hard. For example, try to confirm F=ma, or measure local gravity to the third digit.
You may be assigning more intent than is necessary to explain the (very real) reproducibility problem in psych.
Not to belabor this but to note the irony here: there is probably a similar psychological (ehem) phenomenon that happens to a psyc grad student who lets their presumptions bleed into their interpretation of a measurement.
> The first principle is that you must not fool yourself — and you are the easiest person to fool.
We do have replicable, quantifiable, social psychology. Facebook and Cambridge Analytica are infamous for that. Unfortunately whenever experiments are carried out, you get end up with an uproar over issues of privacy, accountability, and informed consent.
They could be fooling themselves too, not knowingly spreading falsehoods. A lot of of what we call p-hacking can happen by accident by somebody who isn't very good at statistics or just isn't being careful.
50% is reproducibility of experimental studies. There are fields don't even do experiment. There are fields don't even run statistics. There are fields don't even use logic.....
The happiness scale is arbitrary because it lacks reproducibility. The metric system is standardized such that every time you measure the length of something in the physical world that measurement is reproducible.
The problem there is that subject well-being is time-variant. Of course when I ask you at 3 week intervals "how are you feeling?", I'm going to get different answers. If I ask you 3 seconds apart, though (ignoring you getting annoyed at the question), would you not expect consistent results?
> The problem there is that subject well-being is time-variant.
> If I ask you 3 seconds apart, though [...] would you not expect consistent results?
I completely agree with your original comments about lazy writing by the OP. But these all seem besides the point.
Our bodies and minds go through all sorts of states, some cognitively introspectable, some not.
"Happiness", whatever it may be, is what it is and need not conform to your presumptions. That's the point of studying it. Nothing about its fluctuations or the way these are felt by an individual are a problem per se with the research. It just means it's hard to do, and we may not know a whole bunch about it.
Of course it's subjective -- this is the very point, to measure subjective experience.
This point seems to slip through these types of discussions, because people want to keep changing the focus of the research. When you change the topic from subjective experience to, say, neural properties, you're not studying the same thing anymore.
There are plenty of measures of subjective experience of happiness. We can debate the merits of these measures, but they exist. They're reproducible and you can scale them over time or across people.
If someone says they are miserable, and rates themself a 1 on a scale of 1 to 5, this has to be subjective. Are they lying? Perhaps, but then too maybe that radio signal you obtained is a microwave next door.
Units on many psychological measures could be obtained (see test equating) but there's not enough agreement on which measures to use, and in fact, use of multiple measures is encouraged because of variation in what might be an appropriate target of study (hedonic versus eudaimonic well-being for instance). Units in psychology are somewhat similar to where units of temperature were in the 18th or maybe 19th century.
Agree that "arbitrary" was a poor word choice, but it seems as though he meant something like "subjective", which is consonant with the rest of the article.
I think differentiating subjective scales from objective scales isn't terribly fraught, and treating subjective measures as less rigorous than objective measures seems correct to me.
Calling happiness subjective feels weird to me. It's not like "How would you rate The Avengers?", I think asking "How would you rate how you feel at this moment?" is asking the subject to measure something objective about their well-being, no? Maybe I'm oversimplifying it.
I mean, all observations involve a subject. The question is whether there are other subjects that can observe an object and reach consensus about the object. If yes, then, in my view, it's objective. If not, then it's purely subjective.
I go for a run most days and my watch asks me how I feel afterward. I don't answer, because I really have no idea whether my "Good" answer one day corresponds to a "Good" answer on another day. Often, it probably doesn't. In my view, talking about subjective well-being is anything but simple.
It’s subjective because it cannot be universally and independently measured.
It’s not possible to measure the happiness of two individuals such that I can compare them against each other quantitatively and define who of the two is happier.
I can do that, however, with basically every physical measurement.
It is whatever the scale decides it is. A unit of mass isn't anything, either, unless you decide to use Planck units. But we have myriad units of emergent phenomena. This is just on a higher level of abstraction, and so it is harder, but I don't believe it's impossible.
Typically, you'd do Measurement System Analysis (MSA)[1] which includes things like repeatability, reproducibility, drift and linearity. A standard traceable to an authority such as NIST is needed to do this.
For length, MSA can be easily conducted. For happiness, what metrology system are you going to use? What's the proposed measurement method?
That's a pretty shitty unit. Using those units, it's nontrivial to even compare two measurements made in the same country with the same currency, only one generation apart in time. When dealing with a decent unit like meters, you don't need to choose from one of several competing models of distance-inflation to account for the difference in a meter in 2001 and 2021.
There's no global reference frame for distance or wealth. You can't point to a spot in space and say "the Earth was here 1000 years ago". All you can say is that A is x meters from B, right now. And likewise you can't compare wealth now with wealth 50 years ago - it's not a coherent concept, when you could buy a house on a blue collar wage, but not a smartphone at any price. What you can do is say that person A is twice as wealthy as person B.
But as I describe in my other comment, the value of a dollar varies not only with time but also with location and context. There are places in America today where $200 a month from a blue collar job will keep a roof over your head. In other parts of the country, $200 is worth substantially less for the same purpose.
Say what you want about stellar kinematics, but measuring meters simply is not so fraught as this.
I didn’t say it was a good unit, just that it was one.
That being said, I’d argue “2001 dollars” is a unit, not “dollars”. You’ll often see data in econ journals cite something in that type of unit.
Another angle on this is that comparing wealth across time is nontrivial (and the money isn’t to blame). How do you compare the value of a iPhone in 2020 to a landline in 1980? It’s possible, but nontrivial. Our units (in some messy imperfect way) reflect that (and other factors).
Why though? Why dollars in a particular year, rather than dollars in general? Sure the value of a dollar changes from year to year, but the value of a dollar also changes constantly in any given year too. Over the past year, the value of a US dollar relative to a Euro has fluctuated by more than 10 cents. In fact the relative values of currencies fluctuate constantly, near-enough to instantaneously. But this isn't reflected in the pricing of most consumer goods; the price of common household goods in a grocery store might vary a few times a week, but not thousands of times an hour. So in one context the value of a dollar seems to vary constantly, but in another context the value of a dollar is substantially more stable. So a dollar doesn't even have a set particular value at any instant in time; it depends on what kind of store you're standing in.
If happiness is a metric with units even worse than this, then I see little hope for any scientific study of happiness.
Ok I see, to clarify, I mean at the individual, concrete level, as oppose to statistical, and indirect measures of it. I really doubt there is anything, since it's subjective and we also don't know the underlying mechanisms of the mind which produce it.
That looks statistical analysis of some kind, it gives this example:
> the onset of the COVID-19 outbreak, lowered emotional well-being by 74%.
So it's not like it can assess this number for an individual, at least not without first comparing and contrasting it with every other person in some sample group.
In other words, a true unit of happiness, would allow a completely independent measure of any one individual's current state of happiness. Imagine something like a thermometer for happiness, you point it at someone and it reads out the units of happiness (over-simplifying the application to make the point). Therefore we're not even close to knowing what this is or how to measure it, and the way we really communicate around it is by using our own subjectivity of it and making correlations.
I think that is more like saying the average height.
The ladder question (a common tool for measuring SWB) is this:
Please imagine a ladder with steps numbered from zero at the bottom to 10 at the top.
The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you.
On which step of the ladder would you say you personally feel you stand at this time? (ladder-present)
I'm disappointed that the author didn't at least address his issues with operationalization. Leaving it out makes the peice read like a freshman essay.
The meter - while arbitrary as a UNIT of measurement - is defined. It is the length light will travel in a vacuum in 3.33ns ish. Whereas the unit of happiness has no such definition and varies from person to person.
Of course, once you get to the second, we are now just measuring something, and our unit is based on counting a thing. But how do you measure something that can't be counted?
Psychology uses the scientific method to investigate and understand the world; it's a science.
It's sometimes poorly done, but this is true of all the sciences; malpractice and poor rigour in particular experiments don't invalidate an entire field. It's also sometimes misused by other fields, but this is (again) true of all the sciences - a therapist misapplying a principle doesn't stop psychology being a science any more than an engineer miscalculating makes physics pseudoscience.
Science is about the approach, not the topic or the perception.
That last sentence is really well-put. Science is a method. My wife is an actual scientist (biologist doing things with antibodies that I like 60% understand), and when I described A/B testing stuff on ecommerce sites to try and improve conversion rates, her response was something like "Oh, wow, so you're also doing science."
And hey, as someone who was a psych major I can say that psychology is a much more difficult science than either my wife's work or me trying to improve conversion rates, but that's just because it's dealing with things that are harder to measure than changes in conversion rates or the bindings of antibodies to targets. As long as you're correctly applying the scientific method to it, you're doing science.
> Science is about the approach, not the topic or the perception
Agreed on the approach part; as for the topics: there are topics which are inherently hard to "prove"/falsify, either by lack of sufficient evidence (existence of god(s), UFO-as-aliens etc.) or lack of tooling required to tackle the complexity of interactions (many large scale societal problems, psychology, (geo-)politics etc.).
And while "proper" study of those topics is definitely considered science, insisting that we soon can achieve breakthroughs is most likely misguided. What I mean is that we cannot even map and (even if crudely) simulate a single brain, let alone detailed-enough interactions between 7 billions of people. And that's what's probably required to get some solid answers here.
Absolutely; I'm not disputing that in general, psychology is harder to pin down - any experiments are on something vastly complicated that is really hard to isolate. As a formal discipline, psychology is still relatively young, and so it's going to take a long time to get the kind of insights everyone is excited about.
Particle physics is younger than psychology and yet far more effective; why? There is a qualitative difference between the sciences which generate predictive models and those which cannot.
> Particle physics is younger than psychology and yet far more effective; why?
“Physics” isn’t, though, just carving out of particle physics as a distincg niche within it.
But mostly the difference is particle physics deals with simpler systems in which the parts are easier to isolate.
> There is a qualitative difference between the sciences which generate predictive models and those which cannot.
No, there isn’t; all sciences, including psychology, generate predictive models. There’s a quantitative difference in the degree of uncertaintity expected in predictive models in various sciences which affects testing models, and is a product of the degree of difficulty of isolating the effect modelled from potentially confounding influences.
This definition is concerning because without strict criteria for what is and isn’t science, we welcome topics like phrenology.
Topics like this are, as a whole, not true. While I think psychology is no where near as problematic, the author’s argument that a loose definition of science, like whether the scientific method is employed, can be dangerous.
> This is dangerous because, under such a loose definition, anything can qualify as science. And when anything qualifies as science, science can no longer claim to have a unique grasp on secular truth.
Ultimately, what we define as scientific will impact what we perceive to be truthful. Setting a higher bar for a topic to be labeled scientific will strengthen our grasp on secular truth.
Defining science without reference to the scientific method sounds far more concerning. 'A discipline that uses the scientific method to investigate hypotheses' doesn't seem like a loose definition to me, and it definitely doesn't allow phrenology.
Is a hotdog a sandwich? What is it about humans that make us categorize things and then argue about the categorization? Categories are imperfect shortcuts to thinking about a problem.
Categories and abstraction generally is essential for solving a problem. Furthermore, how we categorize disciplines as scientific or pseudoscientific is very important. From the article:
> But to claim it is “science” is inaccurate. Actually, it’s worse than that. It’s an attempt to redefine science. Science, redefined, is no longer the empirical analysis of the natural world; instead, it is any topic that sprinkles a few numbers around. This is dangerous because, under such a loose definition, anything can qualify as science. And when anything qualifies as science, science can no longer claim to have a unique grasp on secular truth.
Yes. We use categories to describe a system. We categorize an engine into a the ignition system, cooling system, air intake system, ect.. We describe node.js by its categories -- errors, file system, streams, ect.. Systems are cyclic which means humans can pretty well make assumptions of a future state of a system by the current and past state of that system. If we want to know a future state, we need to first describe the system. I really like Robert Pirsig's idea of an analytical knife from "Zen and the Art of Motorcycle Maintenance" to cut up systems into categories or category trees, there isn't a one way to do it but rather many ways to describe a system in categories that are more and less useful.
The slippery slope argument. If we don't hold the line, pretty soon we'll be calling astrology a science. Psychology has the potential to be a science, but it's early and we don't know enough. Electricity wasn't a science until Michael Faraday made it one. On the other hand, astrology has no potential to be a science.
The slippery slope argument is only a fallacy when slipping down the slope doesn't actually happen (or can't possibly follow from the described beginning state). Some slippery slopes do actually exist. For example, if you put your weight over the line, you can literally slip down a slippery slope.
On the subject of categories, they cease to be useful when the contents of the categories can no longer tell you anything about the category itself. The further you get down this axis, the less useful the category is. So any dilution of the strength of a category by overly broad inclusion should be scrutinized.
Let me answer your question with a story about Jaffa Cakes
> In the United Kingdom, value added tax is payable on chocolate-covered biscuits, but not on chocolate-covered cakes.[14][15] McVities defended its classification of Jaffa Cakes as cakes at a VAT tribunal in 1991, against the ruling that Jaffa cakes were biscuits due to their size and shape, and the fact that they were often eaten in place of biscuits.[16] McVities insisted that the product was a cake, and allegedly produced a giant Jaffa cake in court to illustrate its point.[16]
> The court discounted the expert evidence, as it went beyond the capacity of an ordinary purchaser.[17] The product was assessed on the following criteria:[18][19]
* The product's name was regarded as a minor consideration.
* The ingredients were regarded as similar to those of a cake, producing a thin cake-like mixture rather than the thick dough of a biscuit.
* The product's texture was regarded as being that of a sponge cake.
* The product hardens when stale, in the manner of a cake.
* A substantial part of the Jaffa cake, in terms of bulk and texture, is sponge.
* In size, the Jaffa cake is more like a biscuit than a cake.
* The product was generally displayed for sale alongside other biscuits, rather than with cakes.
* The product is presented as a snack and eaten with the fingers, like a biscuit, rather than with a fork as a cake might be. The tribunal also considered that children would eat them in "a few mouthfuls", in the manner of a sweet.
The court was adjudicated by Mr Donald Potter QC, who found in favour of McVitie's and ruled that whilst Jaffa Cakes had characteristics of both cakes and biscuits, the product should be considered a cake, meaning that VAT is not paid on Jaffa cakes in the United Kingdom.[14][20] Mr Potter QC also expressed that Jaffa Cakes were not biscuits.[21]
The Irish Revenue Commissioners also regard Jaffa cakes as cakes, since their moisture content is greater than 12%. As a result, they are charged the reduced rate of VAT (13.5% as of 2016).[22]
Sure. Another post on the front page now is about trees[1]. Where's the line between a short tree and a bush? We humans see the difference, but biology (a hard science) shows that using their classification rules there is no difference between a tall bush and a short tree.
If your field re-defines a commonly used term to mean something very precise, obviously you're going to encounter problems when you try work backwards. "Tree" in the meaning of "some phylogenetic categorisation that contains elements x, y, z" may not exist in biology, but "tree" in the meaning of "big leafy thing made of wood" exists as sure as anything.
Drawing lines is for scientific language, not general-purpose language.
I get what you're saying, but I think this is an example of when it's okay to dive into semantics. When we urge people to "trust the science", as we've been doing a lot in the last little while, it matters a great deal how we define science.
"Because psychology often does not meet the five basic requirements for a field to be considered scientifically rigorous: clearly defined terminology, quantifiability, highly controlled experimental conditions, reproducibility and, finally, predictability and testability."
Predictability and testability being the big problems. Science is prediction, not explanation. Psychology has a huge replication problem.
Advertising, though, has become a science. Predictability, testability, controlled experimental conditions, quantifiability - that's Google's business.
Biology has a replication crisis almost as bad as psychology. I agree with a lot of these criticisms but I wonder why we don't see articles questioning if biology is a science. Perhaps there was a period in the past where biology was more rigorous, whereas psych has always been really handwavy?
There's not a lot of real predicting in bio research IME (granted only with a couple subfields). A bunch of things are tried and then whatever works is the focus of the publication, with a write up implying there was a clear hypothesis from the start. Of course not all bio labs are like this, but I'd argue not all psych labs are either.
A lot of this is bad incentives and poor training, but human research is especially hard to control. So I think the issue is partially inherent to the field (in both psych and to some extent bio).
Biology is huge. It encompasses everything from neuroscience to zoography. Somebody could probably make a good case for psychology being under the umbrella of biology, if they were inclined.
I'd guess the replication crisis in biology is not evenly distributed among branches of biology; for instance I guess it's much worse in biomedicine than it is ornithology. And even within one branch of the biology, I expect the replication crisis is not evenly distributed. Studies about the behaviors of birds probably reproduce less than studies about the distribution of birds (particularly since the introduction of photography, which removes a lot of ambiguity from the later but not necessarily the former.)
> I wonder why we don't see articles questioning if biology is a science.
Simply because we can't question the results of the field: medicine, vaccines, etc. Whereas for psychology, I fail to think of a single tangible result.
Science definitely involves explanation as well as prediction, otherwise we’d still be iterating on more and more complex epicycles as predictive models for astrophysics. Induction isn’t everything.
The Big Five personality classification (currently being discussed on the front page [1]) has been reproduced and has predictive power. Sure the results are 'mild' compared to the physical sciences, but it's the best (first?) result that's come out of psychology research that actually meets this bar so far. Apparently it was used by Cambridge Analytica during that whole FB scandal, which is not great but validates it at least?
CA was years ago. Google probably has a much more refined model by now. Too bad they aren't sharing it.
You mean predictions that can be tested right now? Unclear why the proposed time horizon is the right one. This standard would have rejected most of quantum mechanics, some of GR, and many other useful theories and explanations when they were first proposed.
Correct. Similarly, one can imagine a point in the future in which technology advances enough to prove/disprove various predictions with regard to psychology.
You and the person you are responding to are in agreement. They were being sarcastic.
Perhaps the root problem is that it is seemingly impossible for psychology to isolate and control for the dependent variable in question: consciousness.
> the ‘hard’ ones (physics, chemistry, biology) considering themselves to be more legitimate than the ‘soft’ ones (psychology, sociology).”
I'd like to add business (economics) to the list of soft ones as well. They are all, in a way, studies of human behavior.
That is not to say that those soft fields dont apply a lot of scientific methods and use techniques discovered in "hard science" fields (statistics, calculus, etc.)
I think in some sense you can split economics as a field. There's the part that deals with mostly mathematical rules - these are things like the supply and demand curve and what they imply on a system. Then you have the part that seems to study human behavior and tries to somehow quantify it. And last, you have what I'd call politics (political activism?), where it's about trying to justify certain political decisions. Sadly, these are all mixed together.
Well the purely mathematical part is... just mathematics. Economics begins when you claim that certain mathematical systems are an accurate model of economic behaviour of humans.
Yep, economics definitely belongs in the social science field.
The problem is, even in the "hard" sciences a lot of research is hardly scientific. When it comes to human behavior it probably could be studied in a more thorough and methodical way, but for now we simply lack the tools. Today's psychology will be considered pseudoscience in the future, same as astrology which comes from a time when we knew nothing about other solar systems.
Whether or not it’s a science, applying the scientific method to psychology has uncovered extremely important findings in areas such as gender, personality, parenting and children, diversity, mental illness, work, marriage, and to a small extent happiness.
The issue with psychology is that it’s 1. relatively new 2. Area that is challenging to work in 3. Many in the field have questionable motives and perform work that lacks rigor.
I don't know why such a short, lightweight, 9-year-old article was plucked from the past and upvoted 50 times onto Hacker News' front page.
> Happiness research is a great example of why psychology isn’t science. How exactly should "happiness" be defined? The meaning of that word differs from person to person and especially between cultures. What makes Americans happy doesn’t necessarily make Chinese people happy.
I would say that the specific cause may differ but the feeling does not. And even the differences in the causes are exaggerated. Sushi may make you happy. A cheeseburger makes me happy. In both cases, our favorite food makes us happy. Paris makes you happy. London makes me happy. In both cases, our favorite city makes us happy. Our parents fighting would make our childhoods unhappy, though the particular individuals who fight would differ. Interests shared with a mate, studies show, makes a marriage happier, though the particular interests may vary from couple to couple.
Yeah, it's hard to measure concretely. But even the most concrete sciences, like physics and astronomy are squishy, just ask quantum physicists. And I see revisions to biology in the news several times a year.
Just because you can't nail down every last fact, doesn't mean that you can't comb through the foam to extract and build a body of knowledge.
Very true. In the end science is simply about empirical observation of reality, measurement, and continual readjustment of beliefs to match those observations. Whether the subject domain can be more or less exactly measured is neither here nor there.
It would be more accurate to say that "Psychology is not 'just' a science."
There are areas of psychology that rely on methods that are not scientific, because their subject of study is too hard to approach in a rigorously scientific way (though that doesn't mean it's not legitimate knowledge creation, it just comes with more caveats).
But there are also areas of psychology that can be, and are studied with scientific rigour, such as with similar experimental designs to biology.
As someone who has formally studied psychology, the main impression this article makes is that the author knows very little about the contemporary academic discipline of psychology, and is just a bit arrogant about it.
> In the philosophy of science and epistemology, the demarcation problem is the question of how to distinguish between science and non-science. It examines the lines between science, pseudoscience, and other products of human activity, like art and literature, and beliefs. The debate continues after over two millennia of dialogue among philosophers of science and scientists in various fields. The debate has consequences for what can be called "scientific" in fields such as education and public policy. [1]
> The demarcation between science and pseudoscience is part of the larger task of determining which beliefs are epistemically warranted. This entry clarifies the specific nature of pseudoscience in relation to other categories of non-scientific doctrines and practices, including science denial(ism) and resistance to the facts. The major proposed demarcation criteria for pseudo-science are discussed and some of their weaknesses are pointed out. In conclusion, it is emphasized that there is much more agreement on particular cases of demarcation than on the general criteria that such judgments should be based upon. This is an indication that there is still much important philosophical work to be done on the demarcation between science and pseudoscience. [2]
Note it's an opinion piece. There are many branches of psychology and some of them have pretty solid foundations. Yes, there are still more questions than answers in many areas, but so is in physics once you get to the boundaries of the micro- and macrocosm (although in psychology, I'd argue, we're still very much behind when compared do physics and other hard sciences).
At the end of the day, what counts is whether the experiments confirm the theory or not. Practically speaking, in the 'applied-psychology' field of psychotherapy there is at least one method, CBT, that has been battle tested and is widely used for curing various disorders such as fobias. From the scientific point of view, no psychotherapeutic study will ever be classified as scientific as it's inherently impossible to conduct a double-blind study (single-blind is the maximum you can get). Nevertheless, for all intents and purposes, CBT is working and is helping people statistically more than a simple talk with a friend or religious rituals (which also have their efficacy levels).
Granted, "For the past few months I felt bad, but now I feel quite good" is not very scientific, but has enormous value for people who are being helped in this way. Instead of stigmatizing psychology as non-science, we should promote approaches that favor reproducibility and proved to be efficient in practice.
So psychology contains a broad range of subjects. Biopsychology (systems neuroscience) is under psychology as much as it's under biology. That's definitely a science. And Cognitive neuropsychology is similar.
Social, developmental, abnormal (mental illness), language development etc. Yes ok they are less of a science. But they still should be studied and how else should you do it?
Psychology is as much a science as biology is.
IN stage one micro economics on the first day the lecturer said: "Economics is a science because it uses mathematics"
Really very sad. Just because psychology (and economics) is not science, does not mean they are useless or untrue. Science is awesome, but not the only path to truth.
I was careless in my use of the word truth. I mean "useful information that can be relied on". I do not mean anything supernatural.
A lot of human knowledge that fits that category does not come from science. Most medicine, for instance. It comes from the experience of clinicians applying their practice and sharing their knowledge.
"five basic requirements for a field to be considered scientifically rigorous: clearly defined terminology, quantifiability, highly controlled experimental conditions, reproducibility and, finally, predictability and testability." says the article.
The truth (from economics) that all else being roughly equal increasing price reduces demand cannot be found under those restrictions.
The author uses a small subset (positive psychology and its nebulous definition of happiness, although the he doesn’t address that those psychologists do define that term) of psychology to denounce the whole field as “not science.”
String theory deals with measurements that are mind-boggling small to the point where experimentation is impossible. String theory cannot be tested in a lab or in any sort of tactile experiment. Experimentation is a critical piece of a science and so since String Theory cannot be tested with the scientific method, all of physics is not a science.
Of course that argument is absurd and so is this article.
Science is a method of using a combination of theorization and observation to model the world in ways that help us predict future observations. Models are built by carefully accounting for (both with theory and statistics) and apportioning systematic variance in the world. We measure, we recognize covariation, and we theorize about the underlying causal relationships that might explain that covariation. By repeating and refining this process, we advance toward better models of the world that can either explain more variance, or explain the same amount of variance with fewer parameters.
Psychology fulfills all of these criteria. Yes, happiness is subjective, but there is systematic variance that can be accounted for. Psychology just tends to study a lot of complex behaviours that have to be measured indirectly, either through self-report or behaviour. But there's still systematic variance, and psychology uses theory to explain that variance using underlying causal mechanisms. Nothing in here is any different than other sciences. Scientists study plenty of things that are latent and cannot be directly observed. That's part of what makes science so powerful -- being able to incorporate those aspects that can't be directly observed into a theory that encompasses both the unobserved and the observed, and explains their relationships with each other.
> I think the educational and psychological studies I mentioned are examples of what I would like to call Cargo Cult Science. In the South Seas there is a Cargo Cult of people. During the war they saw airplanes land with lots of good materials, and they want the same thing to happen now. So they’ve arranged to make things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head like headphones and bars of bamboo sticking out like antennas—he’s the controller—and they wait for the airplanes to land. They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. So I call these things Cargo Cult Science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.
> How does one measure happiness? Psychologists can’t use a ruler or a microscope, so they invent an arbitrary scale.
The author makes it sound like you just pull a scale out of your ass. There are processes that researchers must follow to create a scale to measure something like happiness. If these rules are not followed correctly, you won't get your research published in reputable journals.
Every time one of these hot takes comes up: "field X isn't a science," I have 2 thoughts:
1. Neither is the entire field of mathematics (or philosophy or logic or history, you name it). Not everything needs to be a science (in the "empirical" sense) to have value or some claim to truthiness/rigor.
2. Or "field X doesn't have the perfect predictability/reproducibility of a proper hard science." Sure. But neither does my doctor, and yet the challenges in the practice of applied medicine don't invalidate the entire science of biology. Which pill will cure me, how long do I have to live, what do you think my symptoms mean--will get you an "I don't know but here's my best guess..." from any honest doctor. Turns out it's hard to go from the micro level (say a cell or single organ) to the macro level (the body as a complex biological system interacting with the environment) in any field. And some fields operate entirely at the macro.
Systems that are sufficiently abstract, interactive, adaptive, subjective, or social tend to be harder to make generalized conclusions about, compared to something you can observe in a vacuum or isolate under a microscope or put in a double blind experiment.
In some cases, maybe we're just not at a point yet where we can make super strong claims. How young is the field of psychology? Or of economics? Think back to Freud and the whole pseudoscience of psychoanalysis, and then look at how far we've come. We've progressed on a hard problem the way chemistry has moved on from alchemy.
The challenges inherent in the social sciences shouldn't mean we just throw up our hands and give up. We try to make them more scientific, develop new standardized measurements for them. Happiness is harder to quantify than mass. Should we not bother trying? Perhaps we never get to the point of perfect predictability. Living organisms are hard to predict, much less entire systems of intelligent ones. But we can learn at least something.
Re why this categorization is important - not explicitly mentioned in the article: Science is a useful tool for learning new things, and developing new tech and guidance. By bringing attention to psychology's questionable adherance to scientific processes, you question the value it brings. This is important when evaluating the results of work produced by the field, and what actions to take based on them.
When something is categorized as "science", you make assumptions about it. Categorizing psychology this way is misleading, and devalues the categorization's purpose.
I remember Feynman speaking quite harshly about most psychology towards the end of "Surely You're Joking, Mr. Feynman!". His complaints were largely around the lack of reproducibility and experiment practices universal across the field.
This piece seems to criticize just one subset of psychology - happiness research - and use that to dismiss the entire field. I feel like writing putting one discipline above another should be a bit more vigorous in that dismissal, even if I ultimately agree with the general sentiment.
Reminded of a great NPR podcast from years ago: a man with dark thoughts (about hurting his wife and child) goes to several therapists and is presented with wildly different often polar opposite techniques and approaches to helping him. One therapist even stopped returning his calls. Worth a listen/read.
Well isn't that liable to happen in any medical diagnosis? Two doctors have two different opinions. Does that mean medicine isn't a scientific discipline?
Welcome to another episode of "X, as per my definition of X, is bad - Let's talk about Y, which is another definition of X, but not the one I disagree with".
This article was written just to troll up attention for his book that came out the same year (2012) with a title that makes the bias more obvious: "Feel-Good Fallacies and the Rise of the Anti-Scientific Left."
I've never heard of the guy before, but it only took a minute of googling to find that out.
I recommend people try the "lateral reading" technique when you come across articles like this. Essentially, Google the source to see if it's biased and unreliable like this is. More on lateral reading and the SIFT technique (stop, investigate, find, trace)
https://library.nwacc.edu/lateralreading/sift
Can you expand on how you think this is the case? Looking at the brain to find out what people think seems to me like looking at atoms to see how an engine works.
I saved this HN comment about this topic a few months ago:
“ Correlations are a profound part of our universe.
When observing the universe, humans can never prove any facts about the universe. We can only establish correlations. Correlations between events that occur in our universe is the furthest "truth" we can establish about the universe short of a full on proof.
What this means is that nothing in the physical universe can be proven. Proof is the domain of maths and logic, correlations is the domain of science. Science cannot prove anything, it can only establish correlations and causations.
The reason this occurs is because at any time in the future one can observe an event that contradicts a hypothesis. You can hypothesize that all birds have wings and observe 2 trillion birds with wings but you never know when one day you'll observe a bird without wings disproving your entire hypothesis. That is why nothing can be proven, you can only correlate things through observation.
The other interesting part about correlation is what it isn't: Causation. People often talk about how correlation is not causation but people never talk about what causation is and how to establish it. If I can't empirically use correlation to establish causation how on earth is causation ever formally established? People rarely question this disconnect.
The fact is, causation is rarely formally established but a method does exist and it's subtle.
If I observe that whenever Bob flicks a switch the light comes on then I established that the light coming on is correlated with Bob flipping the switch. This is as far as I can go with just observation.
To establish causation I must make myself both an observer and an entity that is part of the system itself. I have to take control and flip the switch randomly and observe that when I don't flip the switch nothing happens and when I do flip the switch the lights come on.
By doing this I establish causation. To establish causation to higher and higher degrees I need to Cause (keyword) random events and make sure that a cause influences an effect AND absence of a cause and therefore absence of an effect occurs.
Also note that establishing causation is not proof. At any point in time in the future I can flip the switch and the light may not come on which is contradictory evidence for causation.
Causation in the statistical sense is like correlation, you establish it to a degree of confidence but you can never Prove A caused B.
Note that there are ways to test causal hypotheses without intervening.
For example, suppose we wish to test the hypothesis that smoking causes lung cancer via the main mechanism of tar buildup in the lungs, against the alternative hypothesis that smoking is correlated with lung cancer because of a gene that predisposes people to both smoking and lung cancer (this example comes from Judea Pearl’s Book of Why).
If the former hypothesis is true, then we should see a correlation between smoking behavior and tar deposits, and we should also see a correlation between tar deposits and lung cancer even after controlling for smoking behavior. Composing the causal effects at each stage, we can then calculate the indirect causal effect of smoking on lung cancer. If this suffixes to explain the correlation, then that rules out the alternative genetic explanation for the correlation.
Of course, we can always propose ad-hoc further hypotheses that complicate the analysis: maybe the correlation between smoking and tar deposits is itself non-causative, etc.
This only goes to show that scientific inquiry must be done with judgment and with expert domain knowledge, testing plausible hypotheses in good faith. But that’s true for detecting mere correlations too — we can always doubt our instruments, or claim the data is a statistical fluke. And it’s true in randomized controlled trials: it’s conceivable we didn’t properly randomize, for example.
* This (causation as correlation) revelation was highlighted by Hume and this and other work by him had profound influence on Kant (famously awaking him from his "dogmatic slumbers") and scientists like Darwin and Einstein - the latter obviously in a more healthy scientific age when those at the forefront of physics were not so disdainful of philosophers.”
Psychology has a gazillion competing theories for everything. They ought to do a little more “converging” and a little less “diverging” for a bit (to borrow the diamond model from psychology).
> How does one measure happiness? Psychologists can’t use a ruler or a microscope, so they invent an arbitrary scale.
All scales are arbitrary. We measure length in meters for no reason other than the meter is a nicely human-sized measurement. I'd maybe even argue that the definition of a scale is that it's arbitrary, a mapping of /something/ onto the number line chosen in a way that the numbers are within "human" range.
The real difference being highlighted isn't anything to do with measurement, it's just a difference in dimensions. It's very obvious how we can compare 2 things in space-time dimensions, either they happened at different times that we can map onto our time scale, or they occupy different sizes in space that we can map onto our space scale. Emotions aren't quantifiable in these dimensions, but that doesn't mean we cannot create a space in which they are.
If the author would argue that happiness isn't a "thing" in the way "this piece of paper" or "1945" is, I think that argument can be had, and has been taking place over thousands of years of philosophy. To not even raise the question, but (in my eyes) to assume the answer as obvious, is, as I said, lazy writing.