“..We Are Born Free Yet Bound and Shackled by Department of Justice Glenn Leon’s and Dr. Tim King’s Machines of Loving Grace and Slavery with Extra Steps..”
NORMAN J CLEMENT RPH., DDS, NORMAN L. CLEMENT PHARM-TECH, MALACHI F. MACKANDAL PHARMD, BELINDA BROWN-PARKER, IN THE SPIRIT OF JOSEPH SOLVO ESQ., INC.T. SPIRIT OF REV. IN THE SPIRIT OF WALTER R. CLEMENT BS., MS, MBA. HARVEY JENKINS MD, PH.D., IN THE SPIRIT OF C.T. VIVIAN, JELANI ZIMBABWE CLEMENT, BS., MBA., IN THE SPIRIT OF THE HON. PATRICE LUMUMBA, IN THE SPIRIT OF ERLIN CLEMENT SR., EVELYN J. CLEMENT, WALTER F. WRENN III., MD., JULIE KILLINGSWORTH, RENEE BLARE, RPH, DR. TERENCE SASAKI, MD LESLY POMPY MD., CHRISTOPHER RUSSO, MD., NANCY SEEFELDT, WILLIE GUINYARD BS., JOSEPH WEBSTER MD., MBA, BEVERLY C. PRINCE MD., FACS., NEIL ARNAND, MD., RICHARD KAUL, MD., LEROY BAYLOR, JAY K. JOSHI MD., MBA, ADRIENNE EDMUNDSON, ESTER HYATT PH.D., WALTER L. SMITH BS., IN THE SPIRIT OF BRAHM FISHER ESQ., MICHELE ALEXANDER MD., CUDJOE WILDING BS, MARTIN NJOKU, BS., RPH., IN THE SPIRIT OF DEBRA LYNN SHEPHERD, BERES E. MUSCHETT, STRATEGIC ADVISORS
America’s Clockwork Orange: AUSA Glenn Leon’s American Nightmare
The provided text is a collection of blog posts, excerpts, and quotes discussing the US Department of Justice and DEA’s targeting of medical professionals, specifically those treating chronic pain and addiction.
These texts explore are a grime reminder of the unjust persecution of physicians prescribing pain medication, framing it within broader discussions of societal control and ethical implications.
One central theme is the critique of the U.S. Department of Justice’s aggressive approach, likened to a panopticon system of surveillance and control, that has led to the over-criminalization of pain management.
Another key aspect involves the examination of evolutionary biology and complex systems theory to illustrate the limitations of top-down control and its unintended consequences.
The authors use various philosophical arguments, including Searle’s Chinese Room thought experiment, to illustrate the dangers of reducing complex human interactions and moral decisions to simplistic algorithmic processes.
Ultimately, the texts call for a more nuanced and ethical approach to pain management and societal control, emphasizing the importance of individual agency and the preservation of human rights.
General Timeline
“..The whole history of the progress of human liberty shows that all concessions yet made to her august claims have been born of earnest struggle. . .If there is no struggle, there is no progress. Those who profess to favor freedom and yet deprecate agitation are men who want crops without plowing the ground. They want rain without thunder and lightning. They want the ocean without the roar of its mighty waters..” F. DOUGLAS.
Pre-2016: The text refers to a “small group of similarly charged physicians” beginning their research into the criminalization of medical practice five years prior to 2024, suggesting this trend began around 2019. 2016: Addiction medicine gains recognition as a specialty, coinciding with the rise of the opioid epidemic. Law firms, seeking new targets after the tobacco settlements, begin focusing on the pharmaceutical industry.
2019-2024: The DOJ and DEA, under the leadership of individuals like AUSA Glenn Leon and Anne Milgram, intensify their pursuit of medical practitioners, employing tactics reminiscent of surveillance and control described in works like “A Clockwork Orange” and the concept of the Panopticon.
June 2022: The Supreme Court issues a unanimous ruling in the US v. Ruan case, which should have protected physicians from wrongful prosecution but, according to the text, has not.
May 15, 2024: Dr. L. Joseph Parker voices his concerns about the mislabeling of patients suffering from pain and the criminalization of medical practice.
August 15, 2024: The blog post “AMERICA’S CLOCKWORK ORANGE ALL WATCHED OVER BY THE US. DEPARTMENT OF JUSTICE MACHINES OF LOVING GRACE: AUSA GLENN LEON’S AMERICAN NIGHTMARE: PART-1” is published.
1. The Government AI’s provide personalized predictions that could significantly improve patient outcomes. However, metrics like PPV remind us that healthcare AI predictions are not foolproof, particularly in low-prevalence conditions where false positives can become a challenge.
2.The Government AI models seem to offer a robust, adaptive approach. This false dynamic capability may be entirely useless in clinical practice, where many factors, like a new substance use disorder or a change in prescription dose, may decrease risk in non-linear ways.
3. Predictive Analytics or Predictive Paranoia?
Qlarant’s signature achievement is its “predictive analytics” system, which assigns physicians scores based on their supposed likelihood to commit fraud. These scores are:
4. Instead of splitting atoms, Qlarant’s scientists split their time between inventing fraudulent algorithms and patting themselves on the back for identifying “bad actor” physicians based on the deeply scientific principle of “gut feelings.” Their data models, brilliantly opaque and about as reliable as a carnival fortune-teller, determined which doctors were “drug dealers in white coats.” Forget peer review or validation, Qlarant doesn’t need those pesky scientific standards. Their conviction rates speak for themselves! (Spoiler: Conviction does not equal justice.)
THE HUMAN COST
5. While Qlarant focused on inflating its success metrics, the actual opioid crisis spiraled further out of control: Overdose Deaths: Continued to climb, as patients abandoned by their doctors turned to street drugs.
THE STRUGGLE
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6. Veterans and Chronic Pain Patients: Found themselves labeled as “drug-seekers,” driving some to despair and suicide. Illicit Fentanyl: Became the true killer, largely unaddressed by Qlarant’s physician-hunting algorithms.
7. Here’s how Qlarant’s innovative approach to fighting the U.S. opioid epidemic works:
Step 1: Develop algorithms that rate doctors based on arbitrary factors, such as how far their patients travel or how many prescriptions they write. Forget context like rural healthcare deserts or complex chronic conditions.
Step 2: Share these damning, context-free scores with the DEA and DOJ, effectively deputizing government agencies to destroy careers based on junk science.
Step 3: Bask in the glory of “saving lives” while overdose deaths climb, veterans commit suicide due to untreated pain, and patients turn to illicit drugs.
8. But none of this matters to Qlarant. As long as their PowerPoints look good and they can boast about convictions, who cares about actual public health outcomes? What’s Next? The Pill Mill Doctor Project 2.0?
9. This metric is influenced by the prevalence of the condition in the population being studied. For example, in a population where only 5% of patients are at high risk for overdose, even a highly accurate AI model with excellent sensitivity (ability to detect true positives) and specificity (ability to avoid false positives) could yield numerous false positives. In this low-prevalence scenario, the PPV drops, making the Government AI’s positive predictions less reliable.
10. Although the Government’s AI model might successfully detect true high-risk cases, the sheer volume of false positives can lead to unnecessary alarms, potentially overwhelming healthcare providers and patients.
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FOR NOW, YOU ARE WITHIN
THE NORMS
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