The trouble is that they successfuly made people believe social and human science are as reliable as hard science, using statistical data as mathematical proof.
My wife works in University, they are the most left leaning people I ever saw, but are afflicted by their own cognitive incoherence.
For exemple they are against student visa fraud, but don't alert that the student never came as they don't want to be the one responsible. They just hope there are some right leaning people like my wife who will pull the trigger.
There are a lot of common sense ideas around migration that don't bear out in reality.
For example, in the article they start with a survey question:
> (“Do you think that, in your current country of residence, laws on immigration of foreigners should be relaxed or made tougher?”; 7-point scale).
I don't think this is a good question. Consider the Brexit Paradox: more strict immigration policy often increases the immigration rate because foreign workers decide to move into the country permanently. As they risk losing their access to wel paying jobs otherwise. Conversely, relaxing these policies could actually result in less outgroup culture being imported. And yet such a more relaxed policy would be labeled as "pro (im)migration".
The book "How Migration Really Works" by Hein De Haas was a good read. I didn't find it biased or partisan. It slaughters a lot of left and right wing sacred cows. Made me realize how much political time and effort gets wasted on things that won't work.
Statistics about humans only work if the population equals the sample,
if every respondent tells the truth,
and if the quantitative definitions are correctly specified.
In subjects where you never had to put your credibility where your mouth is - the data says whatever you’d like it to say.
Not to butcher Karl Popper early on Monday morning, but a very good guideline for whether a subject area is scientific is if the prediction it makes are falsifiable. If I propose a theory then I should be able to tell you which test result(s) would prove theory wrong.(I know there are critiques of Popper and falsifiability so I’m not presenting it as the be-all-and-end-all of scientific-ness, just a useful yard stick.)
The problem with that heuristic is more basic than Popperian philosophy. It's that researchers are happy to present falsifiable claims that are in fact then later falsified, but the falsifications don't get published by journals or advertised by the press, and university employers don't care that their employees are making false claims.
Many-analysts results don’t prove bias; they often show the effect is under identified and analyst choices flip sign. Best fix: preregistration + multiverse/sensitivity reporting. Public preferences ≠ measured welfare-support effects.
> In general, hard sciences are much more reliable than social sciences because standards are higher and topics are less emotional.
Having read lots of both, I'm not sure that's true. There's no way to prove it because nobody has clear definitions for what the words hard, social, science, standards or reliable mean. But the extreme political bias doesn't go away, researcher degrees of freedom are just as large, the topics are sometimes much more emotional, and a lot of fields you'd expect to be hard are methodologically no different to any social science.
For example, a guy in Wales recently claimed a big payout from a fraud suit he won against the Dana Farber cancer center at Harvard. It'd been publishing fraudulent papers for years, yet either nobody noticed or nobody cared. Climatology tells people that the end is nigh, a message sufficiently distressing to make some psychologically vulnerable people commit suicide. Do any social sciences have an emotional effect that extreme? A lot of the COVID pseudo-science was specifically designed to manipulate people's emotions (e.g. journals rejecting correct papers because fewer people might take vaccines as a result [1]). And epidemiology isn't based on any empirical understanding of viruses or disease. It's just modelling no different to the type described in the article.
Unfortunately, ideology and bad incentives are the same no matter what field you look at. There is a hard/soft distinction to be made, but it's more about how close the field is to engineering. Engineering fields have a lot of movement between public and private sector, which keeps the universities a bit more honest. Maybe other fields like law and finance are the same, I don't know, I never read papers in those.
> A lot of the COVID pseudo-science was specifically designed to manipulate people's emotions (e.g. journals rejecting correct papers because fewer people might take vaccines as a result [1]).
1. What Covid pseudo science are you referring to?
2. How does the x thread you referenced show “journals rejecting correct papers because fewer people might take vaccines as a result”? As I read it, the rejection was because the journal had a higher bar for evidence on claims around herd immunity than the researchers were able to meet. That is, they’d happily publish papers suggesting lower levels of herd immunity, but the papers would require more rigour than that which was provided.
It’s not clear to me that this bar existed just to increase vaccine uptake, but to generally avoid moves towards relaxing interventions based on insufficiently strong evidence (social distancing, mask wearing, etc).
It’s not clear to me what objection one would have to having a high threshold for evidence when publishing research with such high potential to impact public health. That seems like a good thing to me.
The trouble is that they successfuly made people believe social and human science are as reliable as hard science, using statistical data as mathematical proof.
My wife works in University, they are the most left leaning people I ever saw, but are afflicted by their own cognitive incoherence. For exemple they are against student visa fraud, but don't alert that the student never came as they don't want to be the one responsible. They just hope there are some right leaning people like my wife who will pull the trigger.
[flagged]
There are a lot of common sense ideas around migration that don't bear out in reality.
For example, in the article they start with a survey question:
> (“Do you think that, in your current country of residence, laws on immigration of foreigners should be relaxed or made tougher?”; 7-point scale).
I don't think this is a good question. Consider the Brexit Paradox: more strict immigration policy often increases the immigration rate because foreign workers decide to move into the country permanently. As they risk losing their access to wel paying jobs otherwise. Conversely, relaxing these policies could actually result in less outgroup culture being imported. And yet such a more relaxed policy would be labeled as "pro (im)migration".
The book "How Migration Really Works" by Hein De Haas was a good read. I didn't find it biased or partisan. It slaughters a lot of left and right wing sacred cows. Made me realize how much political time and effort gets wasted on things that won't work.
Statistics about humans only work if the population equals the sample, if every respondent tells the truth, and if the quantitative definitions are correctly specified.
If any one of these fails, the meaning collapses.
In subjects where you never had to put your credibility where your mouth is - the data says whatever you’d like it to say.
Not to butcher Karl Popper early on Monday morning, but a very good guideline for whether a subject area is scientific is if the prediction it makes are falsifiable. If I propose a theory then I should be able to tell you which test result(s) would prove theory wrong.(I know there are critiques of Popper and falsifiability so I’m not presenting it as the be-all-and-end-all of scientific-ness, just a useful yard stick.)
The problem with that heuristic is more basic than Popperian philosophy. It's that researchers are happy to present falsifiable claims that are in fact then later falsified, but the falsifications don't get published by journals or advertised by the press, and university employers don't care that their employees are making false claims.
POSIWID (purpose of system is what it does)
Many-analysts results don’t prove bias; they often show the effect is under identified and analyst choices flip sign. Best fix: preregistration + multiverse/sensitivity reporting. Public preferences ≠ measured welfare-support effects.
Good article except for this bit:
> In general, hard sciences are much more reliable than social sciences because standards are higher and topics are less emotional.
Having read lots of both, I'm not sure that's true. There's no way to prove it because nobody has clear definitions for what the words hard, social, science, standards or reliable mean. But the extreme political bias doesn't go away, researcher degrees of freedom are just as large, the topics are sometimes much more emotional, and a lot of fields you'd expect to be hard are methodologically no different to any social science.
For example, a guy in Wales recently claimed a big payout from a fraud suit he won against the Dana Farber cancer center at Harvard. It'd been publishing fraudulent papers for years, yet either nobody noticed or nobody cared. Climatology tells people that the end is nigh, a message sufficiently distressing to make some psychologically vulnerable people commit suicide. Do any social sciences have an emotional effect that extreme? A lot of the COVID pseudo-science was specifically designed to manipulate people's emotions (e.g. journals rejecting correct papers because fewer people might take vaccines as a result [1]). And epidemiology isn't based on any empirical understanding of viruses or disease. It's just modelling no different to the type described in the article.
Unfortunately, ideology and bad incentives are the same no matter what field you look at. There is a hard/soft distinction to be made, but it's more about how close the field is to engineering. Engineering fields have a lot of movement between public and private sector, which keeps the universities a bit more honest. Maybe other fields like law and finance are the same, I don't know, I never read papers in those.
[1] https://x.com/mgmgomes1/status/1291162360657453056
> A lot of the COVID pseudo-science was specifically designed to manipulate people's emotions (e.g. journals rejecting correct papers because fewer people might take vaccines as a result [1]).
1. What Covid pseudo science are you referring to?
2. How does the x thread you referenced show “journals rejecting correct papers because fewer people might take vaccines as a result”? As I read it, the rejection was because the journal had a higher bar for evidence on claims around herd immunity than the researchers were able to meet. That is, they’d happily publish papers suggesting lower levels of herd immunity, but the papers would require more rigour than that which was provided.
It’s not clear to me that this bar existed just to increase vaccine uptake, but to generally avoid moves towards relaxing interventions based on insufficiently strong evidence (social distancing, mask wearing, etc).
It’s not clear to me what objection one would have to having a high threshold for evidence when publishing research with such high potential to impact public health. That seems like a good thing to me.