Skip to main content



March Update — March 10, 2026

At the Metsu today I ran into the bike guy, Bruce, and another man whose name I didn’t catch.

During dinner I talked with Sue, a Black woman who is new there. She said she was a friend of Liz. I implied that I knew Liz, although I’m not completely sure that I do. There are only so many regulars around there, so it’s possible I’ve seen her before. It might even have been the same Liz—or Lisa—I noticed when I first walked in earlier.

Sue and I started talking about movies, and then the conversation drifted into the Epstein case. She asked a lot of questions and seemed genuinely curious, a bit like Roger when he gets into a topic. I told her I’m not an expert, but I explained the generally accepted account rather than the speculative spy stories that circulate online.

I explained that the way Jeffrey Epstein operated, according to investigations and court records, relied heavily on grooming and normalization. Wealthy environments often include attractive young people working in roles like hospitality, promotion, or service—waitresses, event staff, promotional models at car shows, and so on. Because that kind of environment is common around wealthy people, the presence of young women doesn’t immediately raise suspicion.

That normalization made it easier for exploitation to occur without people immediately recognizing what was happening. Some girls were reportedly recruited by other girls who had already been drawn into Epstein’s circle. I pointed out that using a female intermediary can make new recruits feel safer or less suspicious because it lowers the perceived threat.

Sue already knew about Ghislaine Maxwell and how prosecutors argued she played a role in recruiting and grooming girls for Epstein. We talked about how that tactic—using someone who appears trustworthy to introduce others—is unfortunately a common manipulation strategy in many kinds of exploitation.

Later I took a taxi home. On the ride back I talked with the driver about movies and then about politics.



Comments

Popular posts from this blog

Math

Math tutoring services popular as public schools struggle with poor math scores https://www.ctvnews.ca/canada/math-tutoring-services-popular-as-public-schools-struggle-with-poor-math-scores-1.3717879  Spirit of Math --private tutoring companies  Oxford Learning program -Standardized test scores down and tutoring goes up!  EDIT TO HERE Abbas says  "One of our concerns, which we've heard from many parents, is that once (students) get to high school, all of a sudden they are flabbergasted by the amount of math or kind of math they need to do." -Toronto Star, Peter Goffin, The Canadian Press Published Tuesday, December 12, 2017 The rise in enrolment at such programs coincides with a decline in math scores on standardized tests amongst elementary students in the province. Tutoring companies like Kumon and Oxford Learning say they help students develop independent learning ...

Security‑review site reports it as “suspicious website”

  What it claims SoulmateMeets presents itself as an online platform for connecting people through meaningful, heartfelt communication and potential romantic relationships. soulmatemeets.com On its signup page it states you can browse profiles, like/react, chat, and engage at your own pace (casual chat → deeper). soulmatemeets.com Free to register, but features (especially messaging/chat) appear to be paid/credit‑based. Trustpilot +1 ⚠️ Red flags & concerns The website is very new: domain registration as of May 6 2025. Gridinsoft LLC +1 Ownership info is unclear (WHOIS shows proxy) and trust‑scoring sites flag it as low reliability. ScamAdviser +1 User reviews are heavily mixed. On Trustpilot the average is around 2.9/5 and many complaints involve high cost, bots/fake profiles, or lack of genuine connections. Trustpilot Security‑review site reports it as “suspicious website” with a trust score of 1/100 in one analysis.  Gridinsoft LLC Many user ...

IQ Chart: Human Intelligence, Animal Comparison & AI Capabilities

  IQ Chart: Human Intelligence, Animal Comparison & AI Capabilities Ed Scholz · Follow 2 min read Range: 0 to 250 #1–0–30 Human Cognitive Abilities : Severe cognitive impairment; limited to basic survival tasks. Animal Comparison : Basic reflexive behaviors (e.g., instincts). AI Capabilities : Extremely limited, unable to solve problems. Notable AI Systems : None. Notable Examples : None. #2–30–50 Human Cognitive Abilities : Limited cognition; significant difficulty with simple tasks. Animal Comparison : Rudimentary problem-solving but no abstraction (e.g., rats). AI Capabilities : Basic pattern recognition, no reasoning. Notable AI Systems : None. Notable Examples : None. #3–50–70 Human Cognitive Abilities : Below average; struggles with simple tasks. Animal Comparison : Basic task learning but lacks reasoning (e.g., rats). AI Capabilities : Early speech recognition and basic automation. Notable AI Systems : ELIZA. Notable Examples : None. #4–70–85 Human Cognitive Abilities : ...