228C. What is Threat and How is it Used?
Women increasingly feel threatened by men. Men increasingly feel threatened by women. A useful discussion of threat demands rigorous definitions of what it is and what causes it.
I’ve been interested in the physiology of threat going all the way back to my laboratory research at the Brain Research Institute in 1989 at UCLA. I wrote the first paper on threat generation in games in 2015, Secrets of F2P: Threat Generation. Threat is a key element of dopamine stimulation in games, but in that paper I was focusing on using threat to force players to spend. This can be especially problematic in games that children can access as they can have their physiology permanently altered by early exposure to threat. Epigenetic changes can even be passed on to the children of threatened children.
The mechanism was typically to threaten the players in the game, and then to charge for “protection” from that threat. A well known example was Clash of Clans (Super Cell) and the sale of “protection” shields. Mobsters used to threaten communities and charge for “protection”. Now we have social media companies using threat generation to increase engagement and addiction. Meta and Google have already been successfully sued over the harm this causes users. I followed that paper up with a paper on threat generation in social media.
Moving from games to social media, we now have a business model that pays content creators to generate threatening content for these platforms. The increased threat/engagement drives advertising spend, but at a cost to public health that I am increasingly shining a light on. Now it seems to be a major factor in Demographic Collapse, which will have catastrophic effects on the global economy. I will investigate that further in the next paper on the possible causes of the misandry epidemic.
I proceed here by breaking down threat into four types, which I will then explain in detail:
Bullying: Here the threat is typically coercive in order to force some outcome: a payment, sexual submission, silencing someone, persuading someone to stop competing for a job or academic role, etc. Game threats generally fall in this category. Non compliance can lead to one of the next two types of more dangerous threat. At this level usually the threat stops just short of criminal activity or is of the sort that is rarely prosecuted.
Institutional Threat: These are cases where an institution (the police, media, school, company) is recruited to attack the target. This can lead to incarceration or loss of other rights, or reputational harm. Institutional threat is possibly even more dangerous than kinetic threat as even dying might not remove the threat (due to eternal reputational harm).
Kinetic Threat: A direct physical assault on another. The brandishing of a deadly weapon, even if not used, would fall in this category. The use of chemicals/poison or even more exotic weapons would still fall in this category despite not being what we would think of as physical.
Performative Threat: The use of false or exaggerated claims to bring positive attention to the perpetrator and/or harmful attention to the target. Witch hunts from the 18th century are an early example. Today social media companies have fully automated this process and it is built right into their business models.
None of these threats are exclusive, and a vigorous threat often will cross into multiple lanes of attack. Three additional concepts that are useful here:
Proportionality: Threat is not a binary. The amount of threat matters. In early American days if a black or Native boy looked at a white woman wrong, or if the woman wanted to obscure romantic complicity, the woman could say she felt threatened by the way she was being looked at. This could lead to the boy being beaten or even lynched. Here even if there was some evil intent to the “look”, the response is completely disproportionate to the offense. Examples include Emmitt Till (1955, age 14), Ernest Collins and Benny Mitchell (1935, age 15 and 16), Mack Ingram (1951, “Reckless Eyeballing”), Wes Johnson (1937). I bring up this history because the UK survey that prompted this series showed a significant racial component in the self-reported misandry, along with women even calling for the death of men on social media (either unblocked or bypassing blocks using “algospeak”).
Stochastic Threat: More often referred to as Stochastic Terrorism, I think the use of the word threat is more appropriate as the world terrorism is overly politicized and subject to a lot of ideology. Related to Supremacy Language, the concept is that sufficient performative or institutional threat can lead to vigilantism by individuals in the community against the target who has been painted as morally deficient. Even if the original intent is to kill or otherwise cancel the target, it involves a degree of separation between the instigator and the manipulated attacker to facilitate a plausible deniability defense. A related concept that doesn’t get much attention yet is Stochastic Suicide. Here by threatening an individual or entire demographic sufficiently through media you can increase the probability or rates of suicide.
Collective Punishment: I understand what it feels like to be attacked, abused, or have people try to kill me. This is usually because of my ethnicity but also because extreme cases of childhood cognition like mine require exorcism by some ideologies. If I was a mean or bitter person, I could argue justification to be upset at entire demographics. The reality is that every population has some bad apples, but most people are relatively good souls. To condemn an entire group because of the actions of a few is collective punishment. It is an example of unethical behavior within the constraints of normative morality. During an armed conflict, collective punishment is a war crime. Thus sexism, racism, bigotry, etc. are considered universally immoral behavior, when the justification is something done by an individual. Religious wars have caused a lot of strife over the centuries, and still are. Our Gender War is on the verge of rising to the same level if we don’t make a strong course correction.
Bullying
This is happening a lot on social media. Gendered hate speech like misandry and misogyny are increasingly common examples, even on LinkedIn. Algorithms seem to be programmed to block misogynistic hate speech but to allow misandrist hate speech.
I’ve had problems with people exposing themselves to me over the years, as I’m sure many women have experienced also. While it isn’t legal, it seems to be rarely prosecuted. In the old days before cell phones, it was a lot harder to prove. Bullying in general tends to leave less physical evidence than other threat types, so keeping people in places you can record them until you put them in the “trusted” basket can be helpful.
Institutional Threat
When I had a fellow nursing student who I had agreed to tutor expose herself to me, I was shocked and ran for my life. I was only 19 and not very experienced in such situations. She responded the next morning by convincing the director of our nursing program to kick me out of the program for being male. She didn’t mention her SA of me, and I overheard her entire conversation with the director. She was very sophisticated in her manipulation.
In that situation I lost my career and medical schools later rejected me on the grounds that if I couldn’t handle nursing school, I would not be qualified for medical school. I would have been better off being shot in the leg with a gun. The perpetrator was never punished.
Once the #believeallwomen movement started, this was an attempt to institutionalize the justice system against men: formal gender supremacy. While usually not written into law, it has been informally adopted in the West. This has triggered an explosion of institutional threat against men, making them increasingly reluctant/cautious about interacting with women due to the threat.
Because false allegations are rarely prosecuted, even when proven false, this behavior has become endemic. This is a very simple way to eliminate a workplace competitor also.
Australia started paying bounties to anyone making SA allegations, so 7 petty criminals racked up $1.3B AUD in bounties before the government realized that 4000 claims of SA against teachers was a bit unlikely statistically. Teaching is a hard job, and statistically it is likely that hundreds of teachers lost their lives due to suicide just from this one scheme, which is likely happening in any country with similar laws.
I would encourage all countries to make false allegations, especially false SA allegations, a much more severe and punishable crime than it is currently.
Kinetic Threat
Kinetic threats are those that can or do lead directly to physical harm or loss of live. When the victim is male, the event tends to be undereported or not reported, or not recorded. Thus official statistics are known-unreliable. Homicides, however, tend to be reported and recorded reliably.
In the USA men are 2.7 times more likely to be the victims of homicide compared to women. In Australia the rate is about 2 to 1, so authorities consider this problematic. For women, because that means a 33% rate for women which is higher than in the USA.
Trans folk in the USA are 2.5 times more likely to be killed than cis folk, but that rate rises sharply to 15 times if the victim is black. This mirrors the pattern I brought up in the Proportionality section above where threat against black folk in the USA has been disproportionately high for centuries.
Since physical threats against men are under reported, the only reliable way to get evidence of it is anonymous self reporting. The UK gender hate study used anonymous self reporting of both binary genders so that’s what makes its data so useful. These sorts of high quality studies are rare because usually kinetic threat against men is ignored by researchers.
An NIH 2018 meta analysis of 28 such research papers involving military personnel found that 21% of men and 13% of women were the victims of IPV. Verbal abuse was included, so this is not purely kinetic.
Perhaps the most inclusive meta research on the subject of gender symmetry in IPV that I could find came from the University of Mississippi in 2023. It showed that when researchers only used police-collected data, women were overwhelmingly more likely to be victims of IPV. This was attributed to police being trained to treat men as the perpetrators in IPV, and under reported male-victim IPV by 85%.
Some examples from that meta analysis:
Riggs and O’Leary (1996) found 18.2% of women compared to 9% of men slapped their partners and 13.2% of women compared to 2.5% of men reported kicking, biting, or hitting their partners, yet conclude similar rates of violence. [example of researcher bias]
McNeely and Robinson-Simpson (1987) conclude that women are “as violent as men” (p. 485) using data that shows women to be more violent than men. [Again, evidence of researcher bias]
Straus and Ramirez (2007) found when only one partner was violent it was twice as likely to be the female as the male (19.0% vs 9.8%).
The Mississippi study concludes that women attack their male partners three times as frequently as the reverse scenario. Both genders report being victims at equal rates, which the author concluded was due to a combination of male under reporting and female over reporting. It also found that in relationships with IPV, it was 50+% likely that it was bidirectional (both partners were hostile).
I don’t think that women are inherently more aggressive than men, but since society has little in the way of guardrails against female aggression (and even encourages it), it happens because it is more acceptable.
If this subject is of interest to you, the full study is well worth the read. If you aren’t used to carefully reading research papers, the 57 page length might be intimidating.
Performative Threat and Psychometric Modelling
Demonizing the opposition has been a staple of politics since the invention of politics. The winner is typically whoever does a better job of exaggerating the threat of their opponents. I was credited by “Bomber” Bob Dornan with his 27th Congressional District win in 1980. Being a regular target of ethnic hate, but being white-passing, I knew exactly what to do to get him elected. I went door to door and visited every voter in his district over the age of 50. I then told them that “The Middle Easterners were coming to get them” and that they needed a strong leader like Bob to protect them.
It was so easy, it was child’s play. Literally, since I was 14 years old in 1980.
The invention of psychometric modeling (PM), first deployed in the 2016 UK Brexit vote by Cambridge Analytica, is so powerful that voters are almost helpless when targetted with it. The effect of a single PM attack is the equivalent of what I did in 1980, but can be automated and does not require an expert. The effect wears off about a week later, but voters with “Buyer’s Remorse” can’t undo their votes.
Now you have social media platforms using algorithmic PM to target users with whatever content they are most vulnerable to. The effects are so powerful, they would seem almost improbable even in a James Bond movie:
TikTok also found that it took 35 minutes to addict a user. Meta’s Instagram “Reels” was designed to copy TikTok. Algorithmic PM allows users to be programmed deeply with whatever Performative Threat the platform wants. It then essentially pays the more evangelical content creators to duplicate the programming across their followers.
When I’m being attacked by Gender Supremacists on LI they tend to hit me with the same talking points and cherry picked defective research studies over and over again. This implies that once one of these talking points proves effective, it gets replicated across thousands or even millions of content creators, reaching potentially billions of viewers.
When the UK study found misandry rates close to 30% in their women, I think that’s new. Certainly nothing like that was going on prior to 2016. I would hold up this huge shift in societal hate to the expert and determined use of algorithmic PM. Once you’ve zombified your users (again, only takes 35 minutes, and many users use these products hours every day), programming them to hate using Performative Threat is far easier than you can imagine anywhere except in a bad “B” mind control themed horror movie.
Where is This Going?
In the next (and final for now) paper in the series I will explain what this mass threat campaign is doing to our species, identify some of the people promoting it and why, and explain how it is going to backfire spectacularly. Stochastic threat is cheap and easy, and difficult to prove, but it has a huge limitation: you can’t control who and how someone will respond to it. Well, not without expertise that these people don’t currently possess.
The result here is going to ultimately be the opposite of what they intended. While I find that tremendously amusing, the overall effect on our people is going to be horrible. So any mirth I’m experiencing is highly tempered.
Note that I had no idea what I would find when I started down this rabbit hole, so what I’m about to write about is not at all where I thought my investigation would take me.