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Wednesday, April 8, 2026

UAE says Iran’s nuclear, military capabilities must be addressed

 

The UAE on Wednesday called for a sustained approach to tackle Iran’s nuclear program, ballistic missiles and full range of threats amid a precarious truce, Bloomberg reported.

It is seeking clarification on Trump’s two-week ceasefire to ensure Iran reopens the Strait of Hormuz unconditionally, the report added.


https://www.iranintl.com/en/liveblog/202604067622

N. Korea says missile test used cluster warhead

 North Korea fired a tactical ballistic missile earlier this week that carried a cluster bomb warhead, the Korean Central News Agency (KCNA) said.

The launch involved the surface-to-surface Hwasong-11Ka missile, which the agency claimed "can reduce to ashes any target" across an area of 6.5 to 7 hectares with what it described as the "highest-density power."

KCNA added that North Korea also tested an electromagnetic weapon system and carbon fiber bombs during the same series of trials.

https://breakingthenews.net/Article/N.-Korea-says-missile-test-used-cluster-warhead/66033300

Lies, damn lies, and statistics on criminal illegal aliens

 by Andrea Widburg

We all know the expression “lies, damn lies, and statistics.” We also know about “garbage in; garbage out.” I kept thinking of those phrases when I read that an organization called “Transactional Records Access Clearinghouse” (“TRAC”), the “gold standard” for information about immigrants, deportations, and crime, quietly changed its methods when Trump returned to office. This was not an insignificant change. The result is that it looks as if Trump, rather than deporting “criminal” illegal aliens, is just engaged in racist deportation policies against immigrants.

In 1989, Syracuse University began the TRAC program. Ostensibly (and I’m getting this from Wikipedia), TRAC is “nonpartisan.” TRAC describes its purpose this way:

The purpose of TRAC is to provide the American people — and institutions of oversight such as Congress, news organizations, public interest groups, businesses, scholars, and lawyers — with comprehensive information about staffing, spending, and enforcement activities of the federal government. On a day-to-day basis, what are the agencies and prosecutors actually doing? Who are their employees and what are they paid? What do agency actions indicate about the priorities and practices of government? How do the activities of an agency or prosecutor in one community compare with those in a neighboring one or the nation as a whole? How have these activities changed over time? How does the record of one administration compare with the next? When the head of an agency or a district administrator changed, were there observable differences in actual enforcement priorities? When a new law was enacted or amended, what impact did it have on agency activities?

Specifically on the subject of immigration, TRAC explains,

And still another area, TRAC-Immigration, deals in depth with how our nation’s immigration laws are enforced in administrative and criminal courts by a wide variety of agencies. Reports include records of individual judges. A reference library containing government immigration studies and a glossary are also maintained.

You can see how TRAC specifically handles immigration reporting here.

Significantly, writes Wikipedia, “Over the years, TRAC has been cited in hundreds of news articles.” Because of its academic, nonpartisan bona fides, you’re supposed to be able to trust TRAC.

As for me, I distrust anything that comes out of academia today. When it comes to Syracuse, while there does not seem to be specific data on its faculty donations to political parties, anecdotal evidence suggests that the faculty is as left-leaning as the rest of American academia (except for Hillsdale and Liberty U). Seventeen years ago, an essay claimed that “Liberal bias runs rampant at the Syracuse University campus, even in places you wouldn’t expect.”

It’s doubtful that it’s gotten better in the Trump era. After all, its alumni include Joe Biden, Kathy Hochul, Donna Shalala, and Aaron Sorkin.

That’s the background for this report from Just The News about TRAC’s subtle change to its analysis about criminal deportations:

The nation’s main independent database for tracking deportation statistics and which is widely cited by media outlets and fact-checkers appears to have recently shifted from tracking detainees with a “criminal record” to “criminal convictions.”

This new classification, which was also adopted by another standard immigration tracking database, provides figures widely cited by media and fact-checkers to suggest the Trump administration is detaining large numbers of illegal immigrants not suspected of breaking additional laws.

Since President Donald Trump took office last year, the Transactional Records Access Clearinghouse, or TRAC, changed how it analyzed immigration enforcement data, to emphasize criminal convictions rather than criminal records, which can include arrests that never result in convictions.

The effect of this new approach to analysis is significant. It allows TRAC to insist that, of the more than 68,000 individuals in ICE custody, almost 74% have no criminal convictions. (All presumably are here illegally, which is a good enough reason to deport them.)

While the point about convictions is technically true, Just The News adds that, in addition to the 26% who already have criminal convictions, 26% have also been criminally charged. Of course, a charge is not the same as a conviction, but the fact that these people are entangled in our criminal justice system (often repeatedly) is significant, useful information.

I’ll end as I began: Lies, damn lies, and statistics. And garbage in; garbage out. To be very clear, what TRAC is doing is neither criminal nor civil fraud. However, the way I see it, it is information manipulation to change public policy by affecting public perceptions. The pipeline from academia to media to political decision-making is utterly corrupt and intended to break America.

https://www.americanthinker.com/blog/2026/04/lies_damn_lies_and_statistics_on_criminal_illegal_aliens.html

Oscar Health (OSCR) Shares Surge After CEO's $12M Stock Purchase

 Oscar Health (OSCR) experienced an 11% rise in its stock price on Wednesday morning following a significant share purchase by CEO Mark Bertolini. Bertolini acquired 1 million shares at $11.92 each, totaling nearly $12 million, as disclosed in a regulatory filing. This transaction increased his stake by 11% to 10.2 million shares. The company's stock had already climbed 7% the previous day after the U.S. government announced a 2.5% increase in Medicare Advantage reimbursements for 2027, surpassing earlier expectations.

https://www.gurufocus.com/news/8782769/oscar-health-oscr-shares-surge-after-ceos-12m-stock-purchase

STAAR Surgical prelim Q1 2026 net sales > $90 m, more than doubling prior-year quarter

 


  • Growth in preliminary Q1 2026 net sales was driven primarily by China.
  • Company expects the strong Q1 2026 sales performance to deliver a meaningful improvement in adjusted EBITDA.

Assertio to be acquired by Garda Therapeutics for $18 per share in cash plus contingent value right

 


  • Assertio completed sale of its non-Rolvedon assets to Cosette Pharmaceuticals alongside the Garda Therapeutics agreement announcement.

No Real People Were Polled: AI Is Now Fabricating What "The Public Thinks"

 The other day Axios ran a piece that cited "findings" that a majority of people trusted their doctors and nurses. Turns out, those "findings" were completely fabricated by a company called Aaru - using AI (causing Axios to issue an editor's note and 'clarification')Aaru uses something they call "silicon sampling," where large language models (the AI) can emulate humans at a fraction of the cost and time required for traditional polling, the NY Times reports.

Silicon sampling isn’t polling. It is the outright fabrication of public opinion by machines - and major news outlets and research firms are now publishing those fabrications as legitimate findings. 

This is not an isolated slip. The technology is being embraced by some of the biggest names in media, polling, and corporate research. Gallup has partnered with the startup Simile to create thousands of AI-generated “digital twins” that stand in for real people. Ipsos is working with Stanford to pioneer synthetic data for public opinion studies. CVS, whose venture arm invested in Simile, is already using these fabricated insights to shape customer strategy. And outlets like Axios are treating the output as news.

The entire point of polling has always been authenticity - capturing what actual humans actually think (after oversampling your preferred party to make it look like as if people like Hillary Clinton).

That process is imperfect and messy. Let’s say a pollster wants to learn how many people in the United States are in favor of a certain policy measure, but the pollster ends up with a survey that includes 80 percent Republicans and only 20 percent Democrats. The pollster may think that in reality the country is closer to a 50-50 split, so the results are rebalanced to reflect that perceived reality. This means that the percentages you read as the results of polling are the output of the model, not numbers from the actual survey data.

The problem is that every model is designed with its own biases, because pollsters disagree about which variables deserve more weight. In 2016, The New York Times’s chief political analyst, Nate Cohn, ran an experiment in which he gave five pollsters the same election poll data. (That included Siena College, which conducts opinion polls for The Times and first acquired the data.)

Mr. Cohn found a 5 percent range of difference among what the five pollsters’ models returned. That range was larger than the margin of error typically associated with random sampling, meaning that the modeling assumptions were meaningfully skewing the results. This is alarming, because it suggests that pollsters can use modeling to nudge polls in a certain direction and influence public opinion itself, rather than merely to report what the public thinks.

Walter Lippmann warned a century ago that democracy depends on an accurate picture of the public will. Traditional polling, however imperfect, at least began with real responses from real citizens. It was expensive, slow, and messy precisely because humans are expensive, slow, and messy. Silicon sampling removes every trace of that mess - and with it, every trace of reality. The models are trained on past data, tuned by the biases of their creators, and prompted to spit out whatever “representative” opinions the client wants to see. The result is not public opinion. It is a mirror of the assumptions fed into the machine.

Fake Polling Also Picked Kamala Harris... 

On the eve of the 2024 election, Aaru ran a full-scale simulation that confidently projected a narrow victory for Kamala Harris. Market researchers now use these synthetic polls to decide product launches and ad campaigns. Policy shops quietly substitute AI-generated “constituent sentiment” for actual feedback. Each time a respected outlet or pollster presents these inventions as fact, they normalize the idea that fabricated data is good enough.

The consequences are already here. When headlines say “a new poll shows,” readers have no way of knowing whether real people were ever asked. Trust in institutions is eroding fast enough without handing decision-makers and journalists an unlimited supply of plausible-sounding fake data. Social science, political strategy, and market research risk becoming elaborate games of digital pretend.

So there's that...

https://www.zerohedge.com/political/no-real-people-were-polled-ai-now-fabricating-what-public-thinks