Founder of www.rationally.io
I'm reading this for the first time today. It'd be great if more biases were covered this way. The "illusion of transparency" one is eerily close to what I've thought so many times. Relatedly, sometimes I do succeed at communicating, but people don't signal that they understand (or not in a way I recognize). Thus sometimes I only realize I've been understood after someone (politely) asks that I stop repeating myself, mirroring back to me what I had communicated. This is a little embarrassing, but also a relief - once I know I've been understood, I can finally let go.
I think kindness is a good rule for rationalists, because unkindness is rhetorically OP yet so easily rationalized ("i'm just telling it like it is, y'all" while benefitting – again, rhetorically – from playing the offensive).
Your implication that Aella is not speaking, writing or behaving sanely is, frankly, hard to fathom. You may disagree with her; you may consider her ideas and perspectives incomplete; but to say she has not met the standards of sanity?
She speaks about an incredibly painful and personal issue with remarkable sanity and analytical distance. Does that mean she's objective? No. But she's a solid rationalist, and this post is appropriately representative.
But see, here we are trading subjective takes. You imply this post is insane. I say that it is impressively sane. Are we shouldering the burden of standards for speaking, writing and behaving sanely?
In other words, you've set quite a high bar there, friend, and conveniently it is to your rhetorical advantage. Is this all about being rational or achieving rhetorical wins?
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Wrt "burn it with fire" - she goes on to say that she can't have frame controllers in her life, not that she plans on committing arson. Her meaning was clear to me. If I detect that someone is attempting coercive control on me (my preferred phrasing), I block them on all channels. This has happened 2x in the last 5 years, since I escaped the abuser. I cut them out of my life with a sort of regret; not because I think they're bad, but because I've determined that continued interaction puts me at risk. This is my personal nuclear option too (like Aella) because I'm not one to block people nor consider them irredeemable.
Perhaps you could re-read that part of her post with principle o' charity / steel manning glasses on.
While I'm at it, your other criticism about normal or praiseworthy traits: she explicitly says "Keep in mind these are not the same thing as frame control itself, they’re just red flags." A red flag doesn't mean "a bad behavior" but rather means a warning sign. As is said elsewhere in the comment section (perhaps by you), some of those red flags might be exhibited by Aspie types or those who have successfully overcome some unhelpful social norms. As a different example, I have a friend who talks quickly, genuinely wants to help out even if there is nothing in it for him, and is polymathic - his rapidly covering lots of intellectual ground and wanting to help me out set off my "bullshitter" red flags. But that isn't the case. He's a good guy. And given that, the aforementioned traits are awesome. Red flags are signals and not necessarily bad behaviors.
"Honestly, this is a terrible post. It describes a made-up concept that, as far as I can tell, does not actually map to any real phenomenon [...]" - if I am not mistaken, LessWrong contains many posts on "made-up concepts" - often newly minted concepts of interest to the pursuit of rationality. Don't the rationalist all-stars like Scott Alexander and Yudkowsky do this often?
As a rationalist type who has also experienced abuse, I value Aella's attempt to characterize the phenomenon.
Years of abuse actually drove my interest in rationality and epistemology. My abuser's frame-controlling (or whatever it should be called) drove me to desperately seek undeniable truths (e.g. "dragging one's partner around by the hair while calling them a stupid crazy bitch is objectively wrong"). My partner hacked our two-person consensus reality so thoroughly that this "truth" was dangerous speculation on my part, and he'd punish me for asserting it.
I think abuse is a form of epistemic hacking. Part of the 'hack' is detection avoidance, which can include use of / threat of force (such as "I will punish you if you say 'abuse' one more time"), he-said-she-said ("you accuse me of abuse, but i'll accuse you right back"), psychological jabs that are 100% clear given context but plausibly denied outside that context, and stupid but effective shit like "this isn't abuse because you deserve it." In my experience, detection avoidance is such a systemic part of abuse that it is almost as if it could all be explained as a gnarly mess of instrumental goals gone wild.
My point is, abuse defies description. It is designed (or rather, honed) to defy description.
I don't know if you'll find this persuasive in the slightest. But if you do, even a tiny bit, maybe you could chill out on the "this is a terrible post" commentary. To invoke SCC (though I know those aren't the rules here), that comment isn't true, kind OR necessary.
Already many good answers, but I want to reinforce some and add others.
1. Beware of multiplicity - does the experiment include a large number of hypotheses, explicitly or implicitly? Implicit hypotheses include "Does the intervention have an effect on subjects with attributes A, B or C?" (subgroups) and "Does the intervention have an effect that is shown by measuring X, Y or Z?" (multiple endpoints). If multiple hypotheses were tested, were the results for each diligently reported? Note that multiplicity can be sneaky and you're often looking for what was left unsaid, such as a lack of plausible mechanism for the reported effect.
For example, take the experimental result "Male subjects who regularly consume Vitamin B in a non-multi-vitamin form have a greater risk of developing lung cancer (irrespective of dose)." Did they *intentionally* hypothesize that vitamin B would increase the likelihood of cancer, but only if 1) it was not consumed as part of a multi vitamin and 2) in a manner that was not dose-dependent? Unlikely! The real conclusion of this study should have been "Vitamin B consumption does not appear correlated to lung cancer risk. Some specific subgroups did appear to have a heightened risk, but this may be statistical anomaly."
2. Beware of small effect sizes and look for clinical significance - does the reported effect sound like something that matters? Consider the endpoint (e.g. change in symptoms of depression, as measured by the Hamilton Depression Rating Scale) and the effect size (e.g. d = 0.3, which is generally interpreted as a small effect). As a depressive person, I don't really care about a drug that has a small effect size.* I don't care if the effect is real but small or not real at all, because I'm not going to bother with that intervention. The "should I care" question cuts through a lot of the bullshit, binary thinking and the difficulty in interpreting small effect sizes (given their noisiness).
3. Beware of large effect sizes - lots of underpowered studies + publication bias = lots of inflated effect sizes reported. Andrew Gelman's "Type M" (magnitude) errors are a good way to look at this - an estimate of the how inflated the effect size is likely to be. However, this isn't too helpful unless you're ready to bust out R when reading research. Alternately, a good rule of thumb is to be skeptical of 1) large effect sizes reported from small N studies and 2) confidence intervals wide enough to drive a trunk through.
4. Beware of low prior odds - is this finding in a highly exploratory field of research, and itself rather extraordinary? IMO this is an under-considered conclusion of Ioannidis' famous "Why Most Published Research Findings are False" paper. This Shinyapp nicely illustrates "positive predictive value" (PPV), which takes into account bias & prior odds.
5. Consider study design - obviously look for placebo control, randomization, blinding etc. But also look for repeated measures designs, e.g. "crossover" designs. Crossover designs achieve far higher power with fewer participants. If you're eyeballing study power, keep this in mind.
6. Avoid inconsistent skepticism - for one, don't be too skeptical of research just because of its funding source. All researchers are biased. It's small potatoes $$-wise compared to a Pfizer, but postdoc Bob's career/identity is on the line if he doesn't publish. Pfizer may have $3 billion on the line for their Phase III clinical trial, but if Bob can't make a name for himself, he's lost a decade of his life and his career prospects. Then take Professor Susan who built her career on Effect X being real - what were those last 30 years for, if Effect X was just anomaly?
Instead, look at 1) the quality of the study design, 2) the quality and transparency of the reporting (including COI disclosures, preregistrations, the detail and organization in said preregistrations, etc).
7. Learn to love meta-analysis - Where possible, look at meta-analyses rather than individual studies. But beware: meta-analyses can suffer their own design flaws, leading to some people saying "lies, damn lies and meta-analysis." Cochrane is the gold standard. If they have a meta-analysis for the question at hand, you're in luck. Also, check out the GRADE criteria - a pragmatic framework for evaluating the quality of research used by Cochrane and others.
*unless there is high heterogeneity in the effect amongst a subgroup with whom I share attributes, which is why subgrouping is both hazardous and yet still important.
Not an answer but a related question: is habituation perhaps a fundamental dynamic in an intelligent mind? Or did the various mediators of human mind habituation (e.g. downregulation of dopamine receptors) arise from evolutionary pressures?