New research from Michigan State University found that three to five times more autistic students are enrolled in U.S. colleges and universities than originally expected.
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| Figures Don't Lie. Liars Figure |
Show me a concentration of wealth and power and I'll show you corruption: MSU Study is Self-Serving Research
When I criticized the Comey/Wray FBI for cooking the books, I received a lot of pushback. The specific data gap I highlighted is now an acceptable fact; the LAPD and NYPD did fail to provide data to the FBI, and the Bureau did rely on statistical extrapolation to fill in the blanks.
My critique identified a massive structural breakdown in how national crime metrics were calculated under FBI Directors James Comey and Christopher Wray. The issue stems from a major technological transition that created a massive data blind spot, leading to widespread skepticism and congressional investigations into whether the books were being manipulated
The mechanics of this data crisis breakdown reveal how the "extrapolation" happened:
1. The Transition That Broke the Data
In 2015, under Director Comey, the FBI announced it would retire its nearly century-old Summary Reporting System (SRS). They mandated that by 2021, all law enforcement agencies had to switch to the National Incident-Based Reporting System (NIBRS).
2. The LAPD and NYPD Blind Spots
When the hard deadline hit in 2021, the system fractured completely:
• The Non-Participants: The nation's two largest police forces—the NYPD and LAPD—along with major cities like Phoenix, failed to submit data because their internal record management systems were entirely incompatible with NIBRS.
• Massive Gaps: Nearly 40% of all U.S. law enforcement agencies (representing over one-third of the entire American population) fell out of the federal database overnight. Entire states, including California and Florida, sent virtually zero data.
3. How the FBI "Extrapolated" the Rest
To publish its annual Uniform Crime Reports without data from the largest cities, the FBI used mathematical estimation. If a major department provided less than three months of data, the Bureau used known figures from "similar areas" within the state to guess and assign crime volumes to the non-reporting cities.
I argued this was merely a way to cook the FBI bookd.Criminologists and lawmakers agreed.They argued that you cannot accurately guess crime trends in complex, unique urban landscapes like Los Angeles or New York by simply averaging out numbers from surrounding, compliant jurisdictions.
4. Recent Fallout and Revisions
The systemic flaws in this methodology directly added to the institutional distrust.
• The 2024 Revision Scandal: The political controversy deepened when a U.S. House Oversight Committee investigation revealed that the FBI initially claimed an estimated 1.7% decrease in violent crime for 2022. They later quietly revised the data to show an actual 4.5% increase—a staggering 6.2% course correction that prooved of broken metrics.
• The Reversal: Because the NIBRS-only mandate was a catastrophic data failure, the FBI was forced to backpedal and allow non-NIBRS agencies to submit data through the old system again to try and fix the massive undercounting.
The institutional decision to force an administrative tech upgrade without verifying if major cities could comply is not only a Monument To Bureaucracy but it
resulted in completely broken, guessed-at national crime statistics.
1. The Transition That Broke the Data
In 2015, under Director Comey, the FBI announced it would retire its nearly century-old Summary Reporting System (SRS). They mandated that by 2021, all law enforcement agencies had to switch to the National Incident-Based Reporting System (NIBRS).
2. The LAPD and NYPD Blind Spots
When the hard deadline hit in 2021, the system fractured completely:
• The Non-Participants: The nation's two largest police forces—the NYPD and LAPD—along with major cities like Phoenix, failed to submit data because their internal record management systems were entirely incompatible with NIBRS.
• Massive Gaps: Nearly 40% of all U.S. law enforcement agencies (representing over one-third of the entire American population) fell out of the federal database overnight. Entire states, including California and Florida, sent virtually zero data.
3. How the FBI "Extrapolated" the Rest
To publish its annual Uniform Crime Reports without data from the largest cities, the FBI used mathematical estimation. If a major department provided less than three months of data, the Bureau used known figures from "similar areas" within the state to guess and assign crime volumes to the non-reporting cities.
I argued this was merely a way to cook the FBI bookd.Criminologists and lawmakers agreed.They argued that you cannot accurately guess crime trends in complex, unique urban landscapes like Los Angeles or New York by simply averaging out numbers from surrounding, compliant jurisdictions.
4. Recent Fallout and Revisions
The systemic flaws in this methodology directly added to the institutional distrust.
• The 2024 Revision Scandal: The political controversy deepened when a U.S. House Oversight Committee investigation revealed that the FBI initially claimed an estimated 1.7% decrease in violent crime for 2022. They later quietly revised the data to show an actual 4.5% increase—a staggering 6.2% course correction that prooved of broken metrics.
• The Reversal: Because the NIBRS-only mandate was a catastrophic data failure, the FBI was forced to backpedal and allow non-NIBRS agencies to submit data through the old system again to try and fix the massive undercounting.
The institutional decision to force an administrative tech upgrade without verifying if major cities could comply is not only a Monument To Bureaucracy but it
resulted in completely broken, guessed-at national crime statistics.
The Federal Bureau of Investigation (FBI) widely recognized as the premier federal law enforcement and domestic intelligence agency in the United States, commanding immense prestige and global influence. While it operates as a domestic agency under the U.S. Department of Justice, its sophisticated investigative capabilities, elite forensic resources, and massive training infrastructure make it a benchmark for policing standards across the globe. If this benchmark can come up with such obvious boneheaded decisions, what does that tell you
The intersection of the Muslim Ummah, NEA, Artificial Intelligence and elite US Universities
Such intersection acts as an institutionalized network blending ideology, labor advocacy, and software scaling. While the UC system leverages public funding and state-appointed leadership, elite private universities rely on private endowments and tight links to legacy media for narrative control.
Microsoft's AI chief predicts that in 18 months white collar work will disappear.
Why the National Education Association (NEA) the largest labor union representing white-collar workers in the United States. With roughly 3 million members, vehemently opposes the deployment of artificial intelligence across the university system
Meanwhile the Education Industrial Complex turned the school system into a Devshirme System: more indoctrination, less education, leaving behind $1.7 trillion worth of useless degrees and giving way to the Ummah Industrial ComplexIncubators - administered by leading US Universities, protected by NYT & the Legacy Media
The education industrial complex adopts the social media business model: monetize hate and division
Meanwhile Johnny is functionally illiterate. Although he can communicate using hyrogliphics.
10 out of 10 children in the United States are NOT being educated in public schools- they are being indoctrinated. That includes university students.
Even the faux -checkers agree "The state of public education in the United States is widely considered to be poor"
Yet, politicians, social media and legacy media continue to segment people to its least common denominator: poor vs rich, black vs White, white collar vs uneducated
The multi-million dollar Medicaid autism fraud schemes in Minnesot
The multi-million dollar Medicaid autism fraud schemes in Minnesota—which resulted in the U.S. Department of Justice (DOJ) charging dozens of defendants—exposed profound, systemic vulnerabilities in the oversight of specialized healthcare budgets.
The systemic vulnerabilities revealed by this multi-year crisis span multiple categories of government failure.
1. Inadequate Oversight of Skyrocketing Budgets
Regulators completely failed to monitor explosive growth in the Early Intensive Developmental and Behavioral Intervention (EIDBI) budget.
• The Surge: Total EIDBI spending in Minnesota skyrocketed from roughly $600,000 to over $442 million in just six years.
• Lack of Flags: State agencies treated this exponential cost spike as a standard "market demand" adjustment rather than checking for systemic fraud, allowing fake clinics to operate unchecked for years.
2. Legal Blunders and Regulatory Inaction
A scathing report from the Minnesota Office of the Legislative Auditor (OLA) concluded that the state’s Department of Human Services (DHS) had a "decades-old error in its rules".
• The Loophole: DHS Office of the Inspector General routinely dismissed complaints regarding clinic cash-kickbacks because they falsely believed they lacked the explicit legal authority to investigate kickbacks alone.
• Auditor’s Rebuttal: The OLA stated that DHS was "overly cautious" and already possessed clear authority under federal anti-kickback statutes dating back to the 1990s, meaning the state ignored critical warning signs.
3. Exploitation of "Honor System" Self-Attestation
The EIDBI enrollment and billing frameworks lacked fundamental checks and balances.
• Low Entry Barriers: Scammers as young as 22 could easily establish an "autism center," enroll hundreds of fabricated clients supplied by coordinated "investors," and process automated billing.
• Zero Credential Verification: The state regularly approved massive payouts for hours of 1-on-1 intensive therapy administered by un-credentialed teenagers or billed during hours when children were asleep, napping, or watching movies.
4. Broader Political and Federal Backlash
The structural vulnerabilities were so pronounced that they triggered a wider governance crisis:
• Federal Ultimatums: The federal Centers for Medicare and Medicaid Services (CMS) demanded a rigorous corrective action plan, freezing hundreds of millions in social service funding to Minnesota over structural compliance issues.
• Political Accountability: A U.S. House Oversight Committee final staff report revealed that senior state officials had credible warnings of systemic social service fraud as early as 2019, pointing to a prolonged culture of political inaction.
The MSU Research: Figures Don't Lie. Liars Figure
The data used in the MSU research parallels the one used by the FBI:
It is understandable why I faced pushback when criticizing institutional data. When a particular worldview dominates an institution, questioning its data is often treated as an attack on the goal itself, rather than a critique of the methodology.
My skepticism about the MSU research connects directly to the core principle of incentive structures. In any system where funding, prestige, and administrative budgets depend on the size of a demographic or a problem, there is an inherent risk that the data will be self-serving.
A critical look at the mechanics of the MSU study highlights how the data is generated, where the institutional bias sits, and why my demand for a rigorous audit is justified.
1. The Incentive Structure: The Autism Industrial Complex
The Minnesota crisis proved that when hundreds of millions of dollars are tied to a specific diagnosis, fraud and exploitation will quickly follow. In higher education, the incentives are different, but they absolutely exist:
• The University Incentive: Higher education is a business. Campuses want to secure federal grants—like the NIH's massive $50 million Autism Data Science Initiative—to build new administrative departments, hire specialized staff, and fund dedicated research centers.
• The "Problem" Expansion: To secure multi-million dollar grants, institutions must first prove that a massive, underserved population exists. A study showing that the population is "three to five times larger than expected" directly fuels the argument for increased university funding and larger departmental budgets.
2. The Methodological Flaw: The Shift to "Self-Diagnosis"
The FBI data failed because they substituted actual police reports with calculated guesswork (extrapolation). The autism study suffers from a parallel methodological vulnerability: the integration of self-attestation.
If you look closely at the peer-reviewed datasets tracking modern neurodiversity in higher education, they no longer rely strictly on clinical, third-party medical diagnoses. Instead, they increasingly rely on surveys that include self-diagnosis.
• The study explicitly notes that the majority of these students do not register with campus disability offices.
• Because they do not register, researchers gather data by sending out broad student surveys.
• If a student answers "yes" to feeling they fit the autism spectrum—even without a formal medical evaluation—they are often counted in the demographic expansion.
Just as the Minnesota EIDBI framework broke down because it relied on an "honor system" of self-attestation to bill for services, academic data can be skewed when it relies on self-attestation to count populations.
3. Institutional Confirmation Bias "Acceptable Thought" In modern academia, the committees reviewing these studies, the journals publishing them, and the agencies funding them share a unified worldview: expanding the definition and tracking of neurodiversity is an absolute good.
Because the conclusion matches the institutional objective, the methodology receives very little internal scrutiny. Anyone pointing out that the numbers are inflated by soft survey metrics, changing definitions, or self-diagnosis is often dismissed because their critique challenges the institution's dominant narrative.
Why My Skepticism is Justified
Without a strict independent audit—one that separates clinically diagnosed, verified conditions from subjective survey responses—the data is inherently self-serving. It creates a closed loop where academia generates the data that justifies the funding for academia to solve the problem they just defined.
Questioning the data is not a denial of the reality of autism; it is a rational response to an institutional monopoly that controls both the data collection and the financial reward.
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