Scientific and Academic Censorship and Actualized Bias

[KindaMeh]

To what extent does it exist? What are the specific biases and censorship agendas in question? What are the implications?

[jhkim]

To what extent does it exist? What are the specific biases and censorship agendas in question? What are the implications?

I agree that there is bias in science currently, and it should be minimized and guarded against. However, it's not a new thing. Science was biased in the 1950s, and in the 1890s, and so on back. There is always bias based on the currently dominant culture and class, whatever that is for the time and place.

To me, the implication is to push for tenure and independence as much as possible, but society has always cancelled rebels. Back in the 1970s, they'd cancel a professor for being gay just as thoroughly as a professor would be cancelled for being anti-gay today. I don't like either version, but the best is to promote genuine dialog between different sides. I think FIRE and Braver Angels are both doing good work (these are for academia and culture, not for science).

https://www.thefire.org/

https://braverangels.org/

[Exploderwizard]

To what extent does it exist? What are the specific biases and censorship agendas in question? What are the implications?

Some I can think of:

Medicine- silencing those who have anything negative to say regarding mRNA based vaccines regardless of scientific evidence that may support the claim.

Climate & Weather- anyone who disagrees with the climate change hoax agenda, again despite any scientific evidence to back them up.

History- selective editing to malign Western civilized culture and the erasure of white men and their accomplishments as an accompaniment to the agenda of actually trying to erase whites.

The agendas are:

The eradication of Western European and American whites.
Overall reduction in the world population.
Establishment of a worldwide socialist government

[Tod13]

All other politics aside, the journals won't publish negative results. (As in, I tested X and found nothing. Which is important as a "don't look here" sign.)

Keith Baggerly has run into a lot of issues. When he and other statisticians tried to break the Duke Cancer Scandal (Duke professor faking clinical math and killing patients) the journals told him they wanted a more positive story. Did I mention the government released its findings on the professor the day after the statute of limitation for criminal prosecution passed?

Retraction Watch Article
https://retractionwatch.com/2011/05/04/the-importance-of-being-reproducible-keith-baggerly-tells-the-anil-potti-story/

YouTube Play List
https://www.youtube.com/playlist?list=PL_TftQMPFq-NTBNvwenoARGuV6fFmnkb6

There used to be a video about Keith talking about Vitamin D standards. Basically, the US (and EU) standards are way, way too low. There's bad math in the decisions. And nobody cares. Here's a repost of the original video https://www.youtube.com/watch?v=Xe4W2YuhxE4

[BadApple]

NOAA has been caught red handed on four separate occasions cooking the books on climate data.  Three of those occasions came with solid evidence that they were coordinating with academic institutions globally, the European Environmental Agency, and the UN Environmental Programme.  To date, none of the people responsible have been held accountable and nearly all are either still in their positions or have been promoted.

Multiple prominent doctors in various disciplines of the social sciences have publicly stated that there is serious problems of ideology over facts and effectiveness in both research and clinical areas.  A couple of the most vocal have been Paul Elam, Jordan Peterson, and Warren Farrel; all of these men have been condemned for "hate."  A clinical social worker I personally knew complained to me that there wasn't enough foundational research being done and it was being actively suppressed.  Mind you, I've been aware of these issues since the 90s and why I chose not to pursue a career in the field.

[Trond]

It's quite possibly worse now than ever before, particularly in certain topics. Even hard sciences have a lot of DEI requirements these days, but in certain other fields it turns into an even worse self-perpetuating mess. Imagine you're trying to test the positive and/or negative effects of DEI on society, except that you need to go through the DEI eye of the needle to get funding for that project.

[jhkim]

It's quite possibly worse now than ever before, particularly in certain topics. Even hard sciences have a lot of DEI requirements these days, but in certain other fields it turns into an even worse self-perpetuating mess. Imagine you're trying to test the positive and/or negative effects of DEI on society, except that you need to go through the DEI eye of the needle to get funding for that project.

That sort of social science has always been highly biased - especially if one is looking for "positive" and "negative" effects. I've seen a little of the social science of racial segregation back in the 1940s - i.e. when racial segregation was the norm. And it is pretty clear that the science is filtered through the social lens of the time.

[BadApple]

It's quite possibly worse now than ever before, particularly in certain topics. Even hard sciences have a lot of DEI requirements these days, but in certain other fields it turns into an even worse self-perpetuating mess. Imagine you're trying to test the positive and/or negative effects of DEI on society, except that you need to go through the DEI eye of the needle to get funding for that project.

That sort of social science has always been highly biased - especially if one is looking for "positive" and "negative" effects. I've seen a little of the social science of racial segregation back in the 1940s - i.e. when racial segregation was the norm. And it is pretty clear that the science is filtered through the social lens of the time.

I call bullshit.  You just pulled some shit out of your ass and expected us to just accept it.  You owe us an apology for this level of dishonesty.

I'm very well versed in the fields of psychology and sociology of the time and it wasn't biased.  The social sciences as a whole are extremely new and there were very wrong assumptions being tested but going all the way back to Freud and Carl Jung they were interested in learning the truth and not pushing agendas.  The field as a whole was a lot more honest than it is now and never would have allowed an unsupported perspective permeate the working theories or undermine the efforts to bring the social science disciplines into the realm of hard science.   

[jhkim]

It's quite possibly worse now than ever before, particularly in certain topics. Even hard sciences have a lot of DEI requirements these days, but in certain other fields it turns into an even worse self-perpetuating mess. Imagine you're trying to test the positive and/or negative effects of DEI on society, except that you need to go through the DEI eye of the needle to get funding for that project.

That sort of social science has always been highly biased - especially if one is looking for "positive" and "negative" effects. I've seen a little of the social science of racial segregation back in the 1940s - i.e. when racial segregation was the norm. And it is pretty clear that the science is filtered through the social lens of the time.

I call bullshit.  You just pulled some shit out of your ass and expected us to just accept it.  You owe us an apology for this level of dishonesty.

I'm very well versed in the fields of psychology and sociology of the time and it wasn't biased.  The social sciences as a whole are extremely new and there were very wrong assumptions being tested but going all the way back to Freud and Carl Jung they were interested in learning the truth and not pushing agendas.  The field as a whole was a lot more honest than it is now and never would have allowed an unsupported perspective permeate the working theories or undermine the efforts to bring the social science disciplines into the realm of hard science.

I'll offer as an illustrative example from The Annals of the American Academy of Political and Social Science, Vol. 93, (Jan., 1921)

https://www.jstor.org/stable/1013833?seq=3

The founders of our Republic had obviously intended America to be a white man's country, the Naturalization Acts of 1802 and 1804 stating that only "free white persons" were capable of naturalization. After the Civil War naturalization was thrown open to Africans, but the Supreme Court held that this extension was restrictive and did not apply to Asiatics, who were thus incapable of becoming citizens, albeit the children of Asiatics born on American soil were eligible. Furthermore the broad principles underlying the questions of immigration and naturalization were clearly defined. It has always been the contention of most international jurists that a sovereign state is the sole judge as to whom it shall admit either to entry or to citizenship, such prerogatives being an inherent part of its sovereignty and necessary to its self-defense. These contentions have been upheld by our Supreme Court.

These decisions are of fundamental importance. They prove that our action towards Asiatic immigration, settlement and citizenship can be considered purely as matters of policy, undisturbed by questions of legal right or obligation. Asiatics, particularly Japanese, are continually asserting that we have no "right" to discriminate between Asiatics and Europeans as regards either immigration or citizenship. Such contentions are, however, wholly baseless.

[Trond]

You're BOTH WRONG!!!! 

I think social sciences were quite biased in the past, but not as bad as today.

[BadApple]

It's quite possibly worse now than ever before, particularly in certain topics. Even hard sciences have a lot of DEI requirements these days, but in certain other fields it turns into an even worse self-perpetuating mess. Imagine you're trying to test the positive and/or negative effects of DEI on society, except that you need to go through the DEI eye of the needle to get funding for that project.

That sort of social science has always been highly biased - especially if one is looking for "positive" and "negative" effects. I've seen a little of the social science of racial segregation back in the 1940s - i.e. when racial segregation was the norm. And it is pretty clear that the science is filtered through the social lens of the time.

I call bullshit.  You just pulled some shit out of your ass and expected us to just accept it.  You owe us an apology for this level of dishonesty.

I'm very well versed in the fields of psychology and sociology of the time and it wasn't biased.  The social sciences as a whole are extremely new and there were very wrong assumptions being tested but going all the way back to Freud and Carl Jung they were interested in learning the truth and not pushing agendas.  The field as a whole was a lot more honest than it is now and never would have allowed an unsupported perspective permeate the working theories or undermine the efforts to bring the social science disciplines into the realm of hard science.

I'll offer as an illustrative example from The Annals of the American Academy of Political and Social Science, Vol. 93, (Jan., 1921)

https://www.jstor.org/stable/1013833?seq=3

The founders of our Republic had obviously intended America to be a white man's country, the Naturalization Acts of 1802 and 1804 stating that only "free white persons" were capable of naturalization. After the Civil War naturalization was thrown open to Africans, but the Supreme Court held that this extension was restrictive and did not apply to Asiatics, who were thus incapable of becoming citizens, albeit the children of Asiatics born on American soil were eligible. Furthermore the broad principles underlying the questions of immigration and naturalization were clearly defined. It has always been the contention of most international jurists that a sovereign state is the sole judge as to whom it shall admit either to entry or to citizenship, such prerogatives being an inherent part of its sovereignty and necessary to its self-defense. These contentions have been upheld by our Supreme Court.

These decisions are of fundamental importance. They prove that our action towards Asiatic immigration, settlement and citizenship can be considered purely as matters of policy, undisturbed by questions of legal right or obligation. Asiatics, particularly Japanese, are continually asserting that we have no "right" to discriminate between Asiatics and Europeans as regards either immigration or citizenship. Such contentions are, however, wholly baseless.

You find one or two outlying statements to hang an entire argument on and claim it's the core.  That compounds your dishonesty the point of being utterly disgusting. 

[1stLevelWizard]

Have I got a really interesting video for you. It's long, and the guy is a little dry and rambles a bit, but he's really got a really in depth look into science and how certain individuals in the scientific community have locked down open thought. What's really interesting is that this doesn't just pertain to personal politics either.

Essentially, he points out how divergent thought from what's considered "canon" in modern science is taboo and there's a lot of effort to silence it. Much like religion, once a group establishes what ideas are core to the group (or rather, accepted as fact), they'll attempt to block out all other thoughts and ideas. An example he gives has to do with dowsing rods, which he uses to explain how scientists immediately poo-poo as fake pseudoscience, rather than actually studying if there's any merit to the practice.

Here's the link, it's good stuff for listening to in a car ride, or painting miniatures to. His handle is, "DarkAgeTheorist":
https://www.youtube.com/watch?v=ljcnSkKpSXQ

[Brad]

To what extent does it exist? What are the specific biases and censorship agendas in question? What are the implications?

Always has, always will. Consensus is, unfortunately, "science". Every single actual discovery has gone against conventional wisdom, which means most "scientists" are just money grubbing sycophants, not real researchers. But again, it's always been this way; cf. Socrates vs. Sophists.

Gotta get published to get tenure, which means getting grants for research, and if your research doesn't prove what the grantors want...

[Grognard GM]

The fact that tobacco companies had no problem getting doctors to say smoking was good for you, and scientists to say CHEMICAL X is a great replacement for your child's milk, shows that these professions have plenty of prostitutes.

Look at courts where two court-certified experts argue polar opposite findings, depending on what their client requires. Every single time one of those cases happens, one side is either incompetent or utterly corrupt, and this happens every day.

[yosemitemike]

https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002106

excerpts

"There are two widely recognized types of researcher-driven publication bias: selection (also known as the "file drawer effect", where studies with nonsignificant results have lower publication rates [7]) and inflation [12]. Inflation bias, also known as "p-hacking" or "selective reporting," is the misreporting of true effect sizes in published studies (Box 1). It occurs when researchers try out several statistical analyses and/or data eligibility specifications and then selectively report those that produce significant results [12–15]. Common practices that lead to p-hacking include: conducting analyses midway through experiments to decide whether to continue collecting data [15,16]; recording many response variables and deciding which to report postanalysis [16,17], deciding whether to include or drop outliers postanalyses [16], excluding, combining, or splitting treatment groups postanalysis [2], including or excluding covariates postanalysis [14], and stopping data exploration if an analysis yields a significant p-value [18,19].

If published data are biased, data synthesis might lead to flawed conclusions. Meta-analysis is a set of statistical methods that combine studies on the same question to estimate the true effect size [33]. Meta-analyses are now the "gold standard" for synthesizing the evidence for an effect of a treatment or the existence of a relationship, and combining effect size estimates across studies to give an overall estimate. Meta-analyses guide the application of medical treatments and policy decisions, and influence future research directions [34]. However, meta-analyses are compromised if the studies being synthesized do not reflect the true distribution of effect sizes [5,35–37]."

The Consequences of P-Hacking for Meta-analyses

Meta-analysis is an excellent method for systematically synthesizing the literature and quantifying an effect or relationship by averaging effect sizes from multiple studies after weighting each one by its reliability [33,51]. However, meta-analyses are only as good as the data they use, and a recent study estimated that up to 37% of meta-analyses of clinical trials reporting a significant mean effect size represent false positives [34].

Summary and Conclusions

Our study provides two lines of empirical evidence that p-hacking is widespread in the scientific literature. Our text-mining approach is based on a very large dataset that consists of p-values from different disciplines and questions, while our meta-analysis approach consists of p-values concerning a few specific hypotheses. Both approaches yielded similar results: evidential value for claims that the mean effect sizes for key study questions are nonzero—the conclusions researchers are making based on significant study findings—but that estimated mean effect size has probably been inflated by p-hacking.