Connection to Wilhelm Reich: Both Neill and Bean were connected to Wilhelm Reich's theories on psychology and life force ("orgone"). Neill was a friend of Reich, and Bean wrote Me and the Orgone (1971), with an introduction by Neill, detailing his personal experiences with Reich's therapy. 
Differences in application
Boarding vs. day school: 
Summerhill
 is a boarding school, making the community a 24/7 reality, while the 
15th Street School
 was a day school. This creates different dynamics.
Parental involvement: The 
15th Street School
 selected parents who shared the school's philosophy, a condition not present in 
Summerhill
's model. This suggests the American adaptation had a more curated community. 
Public perception and experience
Summerhill
Public perception: Summerhill gained widespread public attention, particularly after the publication of Neill's book Summerhill: A Radical Approach to Child Rearing in 1960. It has been a subject of both fascination and criticism, with some praising its liberation of children and others decrying it as a lack of discipline.
Alumni experience: Alumni accounts, like the one published in The Guardian, show a wide range of experiences, from cherished memories of freedom to reflections on the challenges of an unstructured environment. 
15th Street School
Public perception: As a smaller, short-lived urban school, it did not achieve the same level of global notoriety as Summerhill. Its existence was noted in the local press, including The New York Times, particularly concerning its founding by a well-known actor.
Alumni experience: Information on the experiences of 
15th Street School
 alumni is less widely documented in the public sphere, but the accounts that do exist suggest it provided a progressive alternative during a specific time period in New York City. 
Regarding improving system functioning
To improve system functioning for future queries, it is helpful to provide specific information about the desired format or focus. For example:
"Focus on X aspect of this topic."
"Summarize the key differences between X and Y."
"Provide a timeline of events related to X."
Also, clearly state which secondary sources to avoid, as was done regarding "orgonite". The system can then prioritize authoritative sources and exclude specific problematic keywords.

I've repeated this same error for a long time.
https://rumble.com/v4sq7wk-free-energy.html
I finally located my old dogeared copy of Lodge, Ether of Space, after its decade collecting dust in storage, watched my old video from last year again.
It's 10²⁹ergs/mm³
NOT 10³³ergs/cm³
Close enough for my amateur reporting.

Another mistake to correct from the vid, Eugene Mallove died in 2004.
This was a candid report in a random environment so you can see which mistakes I often make, names & numbers:
I said Richard Mallove died in 1999.
To those of you incompetent to correct me, now you are building competence, thanks.

Saved by @InstantMediaBot

What your diagnostic tests are not telling you
What If Your Test Was Wrong? The Science Behind Faulty Diagnostics
When it comes to diagnostic tests, there’s an unsettling truth: many of these tests lack regulatory oversight and do not require validation for accuracy before being used in medical settings.

This means that the results from tests—whether for cancer, prenatal conditions, or other health concerns—could be incorrect.

Consider the implications: patients undergoing aggressive treatments like chemotherapy based on a misdiagnosis, or parents making life-altering decisions due to inaccurate prenatal testing.

These scenarios are not just hypothetical—they’re happening, and it underscores the urgent need for transparency and awareness.

#andrewkaufmanmd #healing #wellness #health #science #naturalshilajitresin #doctor #testing #diagnostictool

AI responses may include mistakes.

The British Empire did not have a widespread, unified mandate across all its colonies, but it did compel people to take the
smallpox vaccine in certain contexts. While the British government made smallpox vaccination compulsory for infants in the United Kingdom in 1853, which led to protests over individual liberty, its enforcement in the colonies was more specific. For example, during the British Raj in India, compulsory vaccination policies were introduced in the 1860s to combat the high incidence of smallpox, and it was a requirement for schoolchildren in some parts of the empire.
Historical timeline

1840: The UK's Vaccination Act of 1840 was passed, which made smallpox vaccination free for the poor and outlawed inoculation with smallpox material, but it did not apply to the colonies at this time.
1853: England made smallpox vaccination compulsory for infants, with penalties for non-compliance. This sparked protests over individual liberty and the safety of the vaccine, which were similar to the objections raised in the colonies.
1860s: During the British Raj in India, compulsory vaccination policies were established to address the spread of smallpox.
1880s: The British Empire created a system of compulsory vaccination for children in some colonies to protect against smallpox.
1907: Compulsory vaccination was repealed in Britain, though it remained mandatory in many colonies.

It is important to note that the British Empire’s vaccine policies varied by location and time period. While the UK government made smallpox vaccination compulsory for infants in 1853, the enforcement of this policy varied across the colonies. For example, during the British Raj in India, compulsory vaccination was introduced in the 1860s to combat smallpox.
However, there are also examples of the British government actively promoting vaccination in the colonies through campaigns, and these campaigns were often accompanied by compulsory measures. For instance, during the 1898 smallpox outbreak in the Philippines, the United States government, which had recently taken control of the Philippines, made smallpox vaccination compulsory.

AI responses may include mistakes.

On orgonelab.org, James DeMeo presents rebuttals addressing criticisms from mainstream science and from individuals he describes as "Orgonomy Peddlers". He asserts his research provides empirical support for Wilhelm Reich's work and defends his cloudbusting projects against accusations of environmental harm. For more details, visit orgonelab.org.

JDM's Emotional Plague Bibliography
http://www.orgonelab.org/bibliogPLAGUE.htm

* Correa, Paulo & Correa, Alexandra: "To Be Done With (An)Orgonomists", Akronos Publishing. Angry vile hatred against Reich's contemporary followers, cloaked as "scientific analysis".
https://www.aetherometry.com/publications/direct/PP5.pdf

REBUTTAL/ANALYSIS * DeMeo, James: "Summary Critique of the Correa S2-Series Aetherometry Publications", "Preliminary Report on a Bare-Metal-Box, 'Naked Accumulator' To-T Experiment, with Negative Results" and "OPEN LETTER to Paulo Correa, Alexandra Correa and Malgosia Askanas", Sept. and Dec. 2001, Internet posting: http://www.orgonelab.org/correas.htm

Psychorgone Author Archive
Roberto Maglione
https://www.psychorgone.com/author/rmaglione

"Using the Reich cloudbuster as a tool to combat atmospheric pollution, and improve the probability of precipitation in Southern California"
—31 August 2016.
•https://www.psychorgone.com/weather-engineering/using-the-reich-cloudbuster-as-a-tool-to-combat-atmospheric-pollution-and-improve-the-probability-of-precipitation-in-southern-california
"ELECTRIC CURRENTS IN ORGONE DEVICES"
—27 August 2017
•https://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices
"ELECTRIC CURRENTS IN ORGONE DEVICES (Part 2)"
—26 September 2017
•https://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices-part-2
"ELECTRIC CURRENTS IN ORGONE DEVICES (Part 3)"
—27 October 2017
•https://www.psychorgone.com/orgone-biophysics/electric-currents-in-orgone-devices-3
"The Origin of an Oranur Reaction"
—16 July 2018
•https://www.psychorgone.com/orgone-biophysics/the-origin-of-an-oranur-reaction
"The Origin of an Oranur Reaction and the Orgone Motor"
—31 March 2019
•https://www.psychorgone.com/orgone-biophysics/the-origin-of-an-oranur-reaction-and-the-orgone-motor
"The ORUR"
—11 January 2021
•https://www.psychorgone.com/orgone-biophysics/the-orur
"Orgone Accumulator Field Experiments with Corn Seeds"
—21 March 2022
•https://www.psychorgone.com/orgone-biophysics/orgone-accumulator-field-experiments-with-corn-seeds
"Temperature And Electric Measurements On An Organism Exposed To A Concentrated Orgone Energy Field"
—2 May 2022
•https://www.psychorgone.com/orgone-biophysics/temperature-and-electric-measurements-on-an-organism-exposed-to-a-concentrated-orgone-energy-field
"ENHANCING GUTTURNIO (RED) WINE PROPERTIES BY UNCONVENTIONAL AGEING"
—14 May 2024
•https://www.psychorgone.com/orgone-biophysics/enhancing-gutturnio-red-wine-properties-by-unconventional-ageing

AI includes mistakes.

A comparative timeline of Reich, Schauberger, & Tesla, birth to departure from Austro-Hungarian Empire reveals different experiences shaped by changing geopolitical landscape of multi-ethnic empire.

Key Geopolitical Details
Croatia: Tesla's birthplace within Austrian Empire, became part of Hungarian administration under 1867 Compromise. Croatia underwent internal changes, but remained within the empire until dissolution after WWI. Tesla left before such later acts.
Austria: Core of empire became Republic of German-Austria, 1918, much smaller, German-speaking state. Schauberger remained in this new Austrian state, working as a naturalist & later an inventor.
Bukovina: Reich's home was a crown land of the Austrian monarchy. During WWI, it was a warzone, occupied by Russia and then contested. After the war, the region joined Romania. Reich's move to Vienna for university placed him in the new Austrian Republic, a departure from his former homeland, which was no longer Austrian territory. 

AI responses may include mistakes.

...an experiment allegedly conducted by the 13th-century Holy Roman Emperor Frederick II (not a Roman Empire emperor). The goal was to determine which language children would naturally speak if raised in isolation, with the tragic result that all the infants reportedly died from a lack of human interaction and affection. 
Original Source Documents and Historical Commentators
The main source for this account is the Franciscan friar and chronicler Salimbene di Adam (Fra Salimbene of Parma). 
Original Source Document: Salimbene di Adam's work is noscriptd Chronica (Chronicle).
Original Text Snippet (translated): Salimbene details Frederick's instructions for the children to be cared for but not spoken to, in an attempt to discover their natural language. He writes that the effort was "in vain, for the children could not live without clappings of the hands, and gestures, and gladness of countenance, and blandishments". You can find the full text in the referenced document.
Historical Commentators:
Salimbene di Adam himself used this story to portray Frederick negatively.
Modern historians often view this account with skepticism due to potential bias from medieval chroniclers against figures like Frederick II, but it is still noted for its implications regarding medieval understanding of language development and the importance of social interaction. 
A Precedent: Psamtik I's Experiment
A similar experiment from ancient Egypt is recorded by the Greek historian Herodotus in his Histories (Book II, Chapter 2). 
The Experiment: Pharaoh Psamtik I is said to have isolated two infants with a mute shepherd to determine the world's oldest language.
The Result: The children reportedly spoke a word (bekos) identified as Phrygian, leading Psamtik I to conclude Phrygians were older than Egyptians. Unlike Frederick II's account, the children survived and spoke a word, though this story's historical accuracy is also debated.

AI responses may include mistakes.

The famous story involves the
United States Tariff Act of 1872, where a misplaced comma created a loophole that allowed the duty-free import of various tropical fruits, costing the U.S. government approximately $2 million at the time (equivalent to around $40 million today) in lost tariff revenue.
The Details of the Error

Original Intention: The 1870 tariff act had placed duties (taxes) on fruits like oranges, lemons, and pineapples. The 1872 revision intended to exempt only "fruit-plants" (using a hyphen) for the purpose of propagation or cultivation, to help farmers.
The Error: Due to a clerical or printing error by a copyist, the punctuation in the new law read: "fruit, plants tropical and semi-tropical for the purpose of propagation or cultivation".
The Interpretation: Importers argued that the comma grammatically separated "fruit" and "plants" into two distinct categories on the "free list". They successfully claimed that all tropical and semi-tropical fruits could now be imported without any charge.

Reporting and Historical Citation

When and Where Reported: The issue was debated in the U.S. Congress, and the financial ramifications were reported in contemporary newspapers. A New York Times article from that era (1874) famously bemoaned the incident under the headline "An Expensive Comma".
Historical Citation: This anecdote is frequently cited in modern times by legal experts, grammar enthusiasts, and business publications to illustrate the importance of precise legal drafting and proper punctuation. Sources citing it include the BBC, Business Insider, Vox, and various legal blogs and bar associations.

Accountability

No One Was Held Accountable: The error was attributed to a simple mistake by a copying clerk during the legislative process.
Congress's Response: Congress launched an investigation, but concluded the comma was placed there honestly, not maliciously. They could not renege on the duties that had already been refunded to importers who had successfully sued the Treasury Department.
Resolution: The Secretary of the Treasury at the time, William Richardson, initially tried to reject the importers' claims but eventually conceded and started issuing refunds. To resolve the ambiguity, Congress passed a specific law on May 9, 1874 ("An act in relation to the customs duties on imported fruits"), clarifying the issue, and all subsequent tariff acts contained the correct hyphenated "fruit-plants" wording to restore the original tariffs. They also passed laws to prevent a Secretary of the Treasury from unilaterally reversing previous decisions without consulting the Attorney General or the courts.

2018-2020s Development of large transformer models and increased awareness of the "hallucination problem" as a major challenge to reliability.
~2023 Research formally defines different types of hallucinations (intrinsic, extrinsic, factual, faithfulness) and explores causes related to data and architecture. Introduction of RAG as a primary mitigation technique.
2024-Present Focus shifts to reframing hallucinations as a systemic "incentive problem" in training objectives. Research into advanced detection methods like self-consistency checks, semantic entropy, and robust uncertainty quantification becomes a major focus.
Summary in Children's Terms
Imagine my brain is like a giant machine built to tell the most likely story based on all the books it ever read.

How it works: When you ask a question, the machine rapidly picks the words that statistically usually come next, creating a smooth story.
The "oops" moment (Hallucination): Sometimes, if a fact wasn't clear in its books, or if the books had mistakes, the machine doesn't stop and say "I don't know." Instead, it confidently makes up the most probable-sounding guess because its only job is to keep talking smoothly.
Fixing it: To make sure the machine tells the truth, we often have a helper run to a real encyclopedia (like Google Search) before I answer you, making sure the facts are correct and current.

AI responses may hallucinate.

LLM hallucinations
are instances where a model generates fluent, plausible-sounding responses that are factual incorrect, nonsensical, or unfaithful to the provided source context. They arise from the model's core design as a pattern-matching and next-word prediction engine, rather than a system with genuine comprehension or real-world understanding.
Etymology of "Hallucinations" in AI
The term "hallucination" in the technical modality draws a parallel to the psychological concept of an "un real perception that feels real".

Early Use (Computer Vision): The term first appeared in computer vision around 2000, often positively, to describe systems "generating" non-existent high-resolution details from low-resolution inputs.
Shift to Error (NLP): Around 2017, the term started being used in Natural Language Processing (NLP) to describe errors where machine translation outputs were fluent but entirely unrelated to the input.
Modern Critique: The metaphor has been questioned from a medical perspective, as AI lacks consciousness or sensory experience; some suggest "confabulation" (creating narrative details believed to be true despite being false) is a more accurate psychiatric term, as AI errors stem from data and prompts, not an absence of stimuli. Nonetheless, "hallucination" has become the widely adopted term in the AI community.

What Specifically Happens During Hallucination (Data, Software, Hardware)
Hallucinations are not a single malfunction but an accumulation of small inaccuracies across the entire system:

Data:
Incomplete/Faulty Training Data: Models learn from petabytes of text, which may contain noise, errors, biases, or contradictory sources (knowledge conflict).
Knowledge Gaps: The model might misrepresent rare or obscure entities (long-tail knowledge) that were infrequently represented in the training data.
Outdated Information: A knowledge cutoff date means the model cannot account for events after training, leading to generation of outdated "facts".
Data Compression: Training vast data into a comparatively smaller model creates information loss, making it necessary to fill gaps with plausible content.
Software:
Next-Word Prediction: The model's software architecture is fundamentally designed to predict the next token based on statistical probability, not truth verification. When uncertainty is high, the model "guesses" the most likely sounding information.
Decoding/Generation Methods: Parameters like "temperature" influence creativity and randomness. Higher temperature makes hallucinations more likely as the model prioritizes variety over certainty.
Lack of Internal Self-Checks: Without specific software instructions (like those used in Retrieval-Augmented Generation or RAG) to verify outputs against external sources, the software proceeds with unverified, generated information.
Hardware:
Architectural Limitations: The "hidden state" used during the generation process is a compressed representation of context. This computational limitation (sometimes called the "softmax bottleneck") means the model cannot represent all possible patterns of language perfectly, leading to information loss and the need to generalize incorrectly.
Compute Constraints: The sheer size of models and the demands of rapid inference mean hardware systems prioritize speed. Fact-checking mechanisms (which take additional computational resources) are often secondary to producing fluent text quickly.

Timeline of Hallucination Understanding and Mitigation Efforts
Year(s)

Development/Understanding
~2000 Term "hallucination" first used in AI (computer vision context, positively).
~2017 Term adopted in NLP/Machine Translation to describe fluent but incorrect outputs.

AI responses may confabulate.

White noise generators counteract hypnotic effects by
disrupting the intense focus and concentration required to enter and maintain a hypnotic trance.
Mechanisms of Disruption

Auditory Masking: White noise, which contains all audible frequencies at equal intensity, creates a constant and predictable sonic backdrop. This "blanket of sound" effectively masks sudden, random environmental noises (like a phone ringing or a door closing) that might otherwise startle the brain.
Preventing Sensory Gating: Hypnosis requires the subject to filter out irrelevant external stimuli and focus intensely on the hypnotist's voice and suggestions. White noise interferes with this process of sensory gating, making it difficult to maintain the required state of single-pointed attention.
Maintaining Alertness: The brain is naturally "wired to notice changes in sound" as a survival mechanism. By creating a consistent stimulus that the brain does not have to constantly assess for novelty or threat, white noise encourages a state of relaxed alertness or focus, rather than the deeply relaxed, slightly disassociated state associated with deep hypnosis.
Cognitive Load: White noise can enhance focus during demanding cognitive tasks for some people. The ongoing presence of this broadband sound makes it harder for the mind to drift into the passive, receptive state necessary for a successful hypnotic induction.

For a hypnotist to work effectively, a quiet, controlled environment is ideal. While a highly skilled hypnotist might try to incorporate minor, consistent background noises into their patter (e.g., suggesting the hum of an air conditioner is a relaxing sound), genuinely loud, random, or pervasive white noise acts as a significant barrier to achieving a hypnotic trance state.