Book of Intelligence - Achieve Changs IQ

[Crusile]

Ur so wrong its embarrasing, the PNAS studys only testing in academic contexts, when even then its scope is small


Also again ur absolutely wrong ur denying that tests, test crystal intelligence and not fluid when ur 1 google search away from knowing most besides WAISE test FI


I mean its embarrasing how u could be this blatantly wrong, especially thinking IQ has no correlation to learning speed, when its the exact opposite

Human Intelligence

This book is a comprehensive survey of our scientific knowledge about human intelligence, written by a researcher who has spent more than 30 years studying the field, receiving a Lifetime Contribution award from the International Society for Intelligence. Human Intelligence takes a...

books.google.com

Intelligence and educational achievement

www.research.ed.ac.uk

Source on learning speed specifically. Ie time spent learning increasing learning speed linearly dependent on iq or not

 

[Crusile]

Does fluid intelligence facilitate the learning of English as a foreign language?—A longitudinal latent growth curve analysis

The relationship between intelligence and learning is still a controversial topic. The study at hand examined, via growth curve analysis, if fluid int…

www.sciencedirect.com

Iq doesn't effect 2ndlanguage learning speed

https://www.sciencedirect.com/science/article/abs/pii/S0361476X23000553#f0015 learning speed is linear

Correlates of individual, and age-related, differences in short-term learning

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individua…

www.sciencedirect.com

"In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability."

 

[Rigged]

Does fluid intelligence facilitate the learning of English as a foreign language?—A longitudinal latent growth curve analysis

The relationship between intelligence and learning is still a controversial topic. The study at hand examined, via growth curve analysis, if fluid int…

www.sciencedirect.com

Iq doesn't effect 2ndlanguage learning speed

https://www.sciencedirect.com/science/article/abs/pii/S0361476X23000553#f0015 learning speed is linear

U really didnt read this huh, that study only examines L2 which is a domain specific skill

Correlates of individual, and age-related, differences in short-term learning

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individua…

www.sciencedirect.com

Only linear for rote memorization or repetitive tasks, for harder tasks ppl with higher FI always have a faster learning curve, also the real world follows the power-law curve

"In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability."

Tasks specific results dont generalize, and it only focuses on verbal and spatial tasks

 

[StupidHedonist_INTP]

Does fluid intelligence facilitate the learning of English as a foreign language?—A longitudinal latent growth curve analysis

The relationship between intelligence and learning is still a controversial topic. The study at hand examined, via growth curve analysis, if fluid int…

www.sciencedirect.com

Iq doesn't effect 2ndlanguage learning speed

https://www.sciencedirect.com/science/article/abs/pii/S0361476X23000553#f0015 learning speed is linear

Correlates of individual, and age-related, differences in short-term learning

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individua…

www.sciencedirect.com

"In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability."

I mean whatever, but for sure an average human learns faster than an animal and it probably just has to be because of the iq difference which proves that higher iq increases learning speed.

 

[StupidHedonist_INTP]

*just has to do

 

[Crusile]

I mean whatever, but for sure an average human learns faster than an animal and it probably just has to be because of the iq difference which proves that higher iq increases learning speed.

IQ is a measure of social class not intelligence. It estimates a persons exposure to iq test question knowledge.

 

[Crusile]

U really didnt read this huh, that study only examines L2 which is a domain specific skill

Only linear for rote memorization or repetitive tasks, for harder tasks ppl with higher FI always have a faster learning curve, also the real world follows the power-law curve

Tasks specific results dont generalize, and it only focuses on verbal and spatial tasks

What do you mean by harder tasks? IQ test questions are non-complex 1 dimensional problems.

 

[Crusile]

simple gamified jobs like machine gunner are most g-loaded while the most complex jobs like air traffic control is least g-loaded. The job with the most g-loaded job performance is probably something repetitive and simple like Toyota factory assembly line worker

 

[Rigged]

IQ is a measure of social class not intelligence. It estimates a persons exposure to iq test question knowledge.

This is outdated and has been refuted ravens progressive matrices and cattells culture fair test are designed to avoid any biases, if iq was solely about social class then it wouldnt predict academic and job performance across all socioeconomic groups

What do you mean by harder tasks? IQ test questions are non-complex 1 dimensional problems.

Iq tests include both simple and complex tasks with different subtests for example matrix reasoning and digit span

simple gamified jobs like machine gunner are most g-loaded while the most complex jobs like air traffic control is least g-loaded. The job with the most g-loaded job performance is probably something repetitive and simple like Toyota factory assembly line worker

this is so blatantly and factually incorrect the g loading of job performace increases with job complexity, the more complex the higher the g loading, repetative jobs like factory work are less g loaded while surgeons are highly g loaded

https://www1.udel.edu/educ/gottfredson/reprints/1997whygmatters.pdf

Ur so wrong and ur making up shit just to be right its dissapointing

 

[Crusile]

This is outdated and has been refuted ravens progressive matrices and cattells culture fair test are designed to avoid any biases, if iq was solely about social class then it wouldnt predict academic and job performance across all socioeconomic groups

Iq tests include both simple and complex tasks with different subtests for example matrix reasoning and digit span

this is so blatantly and factually incorrect the g loading of job performace increases with job complexity, the more complex the higher the g loading, repetative jobs like factory work are less g loaded while surgeons are highly g loaded

https://www1.udel.edu/educ/gottfredson/reprints/1997whygmatters.pdf

Ur so wrong and ur making up shit just to be right its dissapointing

IQ is a weak predictor of job performance, especially complex jobs. IQ is only novely predictive of simple gamified tasks. What am I making up? Why is IQ least predictive of complex military jobs (in the last image i sent)

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

 

[Crusile]

This is outdated and has been refuted ravens progressive matrices and cattells culture fair test are designed to avoid any biases, if iq was solely about social class then it wouldnt predict academic and job performance across all socioeconomic groups

Iq tests include both simple and complex tasks with different subtests for example matrix reasoning and digit span

this is so blatantly and factually incorrect the g loading of job performace increases with job complexity, the more complex the higher the g loading, repetative jobs like factory work are less g loaded while surgeons are highly g loaded

https://www1.udel.edu/educ/gottfredson/reprints/1997whygmatters.pdf

Ur so wrong and ur making up shit just to be right its dissapointing

raven's tests are extremely culturally loaded https://www.researchgate.net/public...utility_of_Raven's_among_Sub-Saharan_Africans

 

[Crusile]

This is outdated and has been refuted ravens progressive matrices and cattells culture fair test are designed to avoid any biases, if iq was solely about social class then it wouldnt predict academic and job performance across all socioeconomic groups

Regressions were essentially homogeneous and, contrary to the claims by those working from a meritocratic perspective, the slope for the low IQ group was steepest (see Figure 4.1). There was no limitation imposed by low IQ on the beneficial effects of good social background on earnings and, if anything, there was a trend toward individuals with low IQ actually earning more than those with average IQ (p = .09). So it turns out that although both schooling and parental social class are powerful determinants of future success (which was also true in Terman’s data), IQ adds little to their influence in explaining adult earnings. (Ceci, 1996: 86)

IQ isn't predictive of success after controlling for social class

 

[StupidHedonist_INTP]

IQ is a weak predictor of job performance, especially complex jobs. IQ is only novely predictive of simple gamified tasks. What am I making up? Why is IQ least predictive of complex military jobs (in the last image i sent)

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

Probably because no one smart wants to serve the military lol

 

[StupidHedonist_INTP]

IQ isn't predictive of success after controlling for social class

Anyways, what's your way of measuring intelligence? A lot of knowledge, fast and good articulation, being able to understand complex topics and theories, good at arguments and debating, what are the best way to know if someone is intelligent, and I think you agree that intelligence cannot be improved if your health is maximised, just your knowledge that makes you appear more intelligent, right?

 

[looks>books]

Key takeaway?

 

[Rigged]

IQ is a weak predictor of job performance, especially complex jobs.

This is blatantly wrong i sent the gottfredson study proving it

IQ is only novely predictive of simple gamified tasks.

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emilkirkegaard.dk

What am I making up? Why is IQ least predictive of complex military jobs (in the last image i sent)

Loading…

onlinelibrary.wiley.com

Loading…

www.officialasvab.com

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

raven's tests are extremely culturally loaded https://www.researchgate.net/publication/323398838_The_Raven's_test_performance_of_South_Sudanese_samples_A_validation_of_criticisms_of_the_utility_of_Raven's_among_Sub-Saharan_Africans

This is so blatantly wrong and that goes against the whole point of ravens, ive read the actual study, the reason it wasnt “culturally fair” was because the sub saharans lacked the knowledge on test taking formats, its the same way older people struggle to take license tests on computer while doing really well on the exact same test when its on paper

Raven's test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn Effect

This paper presents a systematic review of published data on the performance of sub-Saharan Africans on Raven's Progressive Matrices. The specific goals were to estimate the average level of performance, to study the Flynn Effect in African

www.academia.edu

 

[Rigged]

IQ is a weak predictor of job performance, especially complex jobs. IQ is only novely predictive of simple gamified tasks. What am I making up? Why is IQ least predictive of complex military jobs (in the last image i sent)

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

The bell curve : Richard J. Herrnstein : Free Download, Borrow, and Streaming : Internet Archive

archive.org

 

[Crusile]

This is blatantly wrong i sent the gottfredson study proving it

Loading…

emilkirkegaard.dk

Loading…

onlinelibrary.wiley.com

Loading…

www.officialasvab.com

This is so blatantly wrong and that goes against the whole point of ravens, ive read the actual study, the reason it wasnt “culturally fair” was because the sub saharans lacked the knowledge on test taking formats, its the same way older people struggle to take license tests on computer while doing really well on the exact same test when its on paper

Raven's test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn Effect

This paper presents a systematic review of published data on the performance of sub-Saharan Africans on Raven's Progressive Matrices. The specific goals were to estimate the average level of performance, to study the Flynn Effect in African

www.academia.edu

So although the symbols in a test like the RPM are experience-free, the rules governing their changes across the matrix are certainly not, and they are more likely to be already represented in the minds of children from middle-class homes, less so in others. Performance on the Raven’s test, in other words, is a question not of inducing ‘rules’ from meaningless symbols, in a totally abstract fashion, but of recruiting ones that are already rooted in the activites of some cultures rather than others. Like so many problems in life, including fields as diverse as chess, science and mathematics (e.g. Chi & Glaser, 1985), each item on the Raven’s test is a recognition problem (matching the covariation structure in a stimulus array to ones in background knowledge) before it is a reasoning problem. The latter is rendered easy when the former has been achieved. Similar arguments can be made about other so-called ‘culture-free’ items like analogies and classifications (Richardson & Webster, 1996). (Richardson, 2002: pg 292-292)

 

[Crusile]

The bell curve : Richard J. Herrnstein : Free Download, Borrow, and Streaming : Internet Archive

archive.org

Can you explain why complex military jobs are less g-loaded than less complex military jobs?

 

[Crusile]

Anyways, what's your way of measuring intelligence? A lot of knowledge, fast and good articulation, being able to understand complex topics and theories, good at arguments and debating, what are the best way to know if someone is intelligent, and I think you agree that intelligence cannot be improved if your health is maximised, just your knowledge that makes you appear more intelligent, right?

Intelligence, as I have conceived of it, is a dynamic and constantly-developing trait, which evolved through our experiences, cultural backgrounds, and how we interact with the world. It is a multifaceted, context-sensitive capacity. Note that I am not claiming that this is measurable, it cannot be reduced to a single quantifiable measure. And since intentionality is inherent in the definition, this further underscores how it resists quantification and measurability.

Intelligence without IQ: Towards a Non-IQist Definition of Intelligence

3000 words Introduction In the disciplines of psychology and psychometrics, intelligence has long been the subject of study, attempting to reduce intelligence to a number based on what a class-bias…

notpoliticallycorrect.me

 

[Rigged]

@Crusile

This is blatantly wrong i sent the gottfredson study proving it

Loading…

emilkirkegaard.dk

Loading…

onlinelibrary.wiley.com

Loading…

www.officialasvab.com

This is so blatantly wrong and that goes against the whole point of ravens, ive read the actual study, the reason it wasnt “culturally fair” was because the sub saharans lacked the knowledge on test taking formats, its the same way older people struggle to take license tests on computer while doing really well on the exact same test when its on paper

Raven's test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn Effect

This paper presents a systematic review of published data on the performance of sub-Saharan Africans on Raven's Progressive Matrices. The specific goals were to estimate the average level of performance, to study the Flynn Effect in African

www.academia.edu

Learn how to read, bet u havent read a single thing so far if ur resending the thing i replied to already

 

[Rigged]

Can you explain why complex military jobs are less g-loaded than less complex military jobs?

Theyre not, this is a blatant circular reasoning fallacy

 

[Crusile]

Theyre not, this is a blatant circular reasoning fallacy

No your outdated studies dont replicats. Machine gunner(simple task) more g loaded than heli mechanic and air traffic controller (complex tasks)

 

[Rigged]

No your outdated studies dont replicats. Machine gunner(simple task) more g loaded than heli mechanic and air traffic controller (complex tasks)

Yeh wise fold, my studies arent outdated, for a study to get taken down it has to be proven wrong through court the studies u sent are older and u also missinterpreted them on purpose, also no ur wrong machine gunner isnt more g loaded

 

[cyprian_tomaszewski]

well this guide wasnt made for low iq ppl, its a guide i made a long time ago i just decided to post it here

learnt something new about this topic since then that you didn't put into the guide?

 

[Crusile]

Yeh wise fold, my studies arent outdated, for a study to get taken down it has to be proven wrong through court the studies u sent are older and u also missinterpreted them on purpose, also no ur wrong machine gunner isnt more g loaded

Your shitty studies are p-hacked and don't replicate

 

[Crusile]

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

 

[Rigged]

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Is Cognitive Ability the Best Predictor of Job Performance? New Research Says It’s Time to Think Again

Meta-analyses have overestimated both the primacy of cognitive ability and the validity of a wide range of predictors within the personnel selection arena, according to groundbreaking research conducted by Paul R. Sackett and Charlene Zhang, University of Minnesota; Christopher Berry, Indiana...

www.siop.org

This doesnt debunk shit read ur own studies, the study says schmidt and hunter FROM 1998 way before any of my studies was overestimating, not only does this not debunk anything it also doesnt argue against what i was arguing for

 

[Crusile]

Does IQ really predict job preformance?

https://www.tandfonline.com/doi/full/10.1080/10888691.2014.983635

Their collective effect has mainly arisen from their combination in a few well-known meta-analyses. Hundreds of studies prior to the 1970s reported that correlations between IQ tests and job performance were low (approximately 0.2–0.3) and variable (reviewed by Ghiselli, Citation1973). These results were widely accepted as representative of the disparate contexts in which people actually work. Then, Schmidt and Hunter (Citation2003, for an historical account) quite reasonably considered the possibility that the large quantity of results were attenuated by various statistical artifacts, including sampling error, unreliability of measuring instruments, and restriction of range. They devised methods for correcting these artifacts and incorporating the studies into meta-analyses. The corrections doubled the correlations to approximately 0.5. Nearly all studies cited in favor of IQ validity are either drawn from the Schmidt and Hunter meta-analyses or from others using the correction methods developed for them.

https://psycnet.apa.org/record/2024-33488-001?trk=public_post_comment-text

Correcting for unreliability in the criterion and correcting predictive studies for range restriction produces a mean corrected validity of .22 and a residual SD of .11. While this is a much smaller estimate than the .51 value offered by Schmidt and Hunter (1998), that value has been critiqued by Sackett et al. (2022), who offered a mean corrected validity of .31 based on integrating findings from prior meta-analyses of 20th century data. We obtain a lower value (.22) for 21st century data. We conclude that GCA is related to job performance, but our estimate of the magnitude of the relationship is lower than prior estimates. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Complex jobs/tasks in the military are much less g-loaded than simple jobs/tasks (2024)

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psycnet.apa.org

 

[Crusile]

This doesnt debunk shit read ur own studies, the study says schmidt and hunter FROM 1998 way before any of my studies was overestimating, not only does this not debunk anything it also doesnt argue against what i was arguing for

High g-loading of complex military job/task performance does not replicate. I want you to prove that complex tasks are more g-loaded than simple tasks since your argument is "Yes learning speed is linear for memorization or repetitive asks, but for harder more complex task, higher IQ people always have a faster learning curve".

 

[Rigged]

Does IQ really predict job preformance?

https://www.tandfonline.com/doi/full/10.1080/10888691.2014.983635

Talks about studies pre 70s

https://psycnet.apa.org/record/2024-33488-001?trk=public_post_comment-text

.22 validaty coefficient supports my point .22 is not zero .22 corelation is big in psychology

Complex jobs/tasks in the military are much less g-loaded than simple jobs/tasks (2024)

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This isnt true u resent what ive already debunked and replied to


Ur such a weirdo for just trying to argue without even reading ur own studies

 

[Rigged]

High g-loading of complex military job/task performance does not replicate. I want you to prove that complex tasks are more g-loaded than simple tasks since your argument is "Yes learning speed is linear for memorization or repetitive asks, but for harder more complex task, higher IQ people always have a faster learning curve".

I did already sent the gottfredson research paper

 

[Crusile]

I did already sent the gottfredson research paper

Yes,, this was grossly p-hacked and did not replicate "Hunter (1983, 1986) demonstrated this clearly with U.S. Employment Service General Aptitude Test Battery (GATB) validitydata for 5 15 occupations (see also Gutenberg, Arvey, Osburn, & Jeanneret,1983)."

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This (2024) shows that less complex military jobs had a bigger g-loading that simple military jobs

 

[Swarthy Knight]

What you IQcels even do with all this info jfl

 

[Crusile]

Talks about studies pre 70s

.22 validaty coefficient supports my point .22 is not zero .22 corelation is big in psychology

This isnt true u resent what ive already debunked and replied to


Ur such a weirdo for just trying to argue without even reading ur own studies

Wrong, if other predictors of jobs performance outperform IQ, then IQ a weak predictor. For example, job specific knowledge tests are more predictive than IQ tests, adding iq tests yields no predictive utility. IQ = INVALID.

Standardized tests and subjective specific tests (that have been use to show that learning speed is linear) are also predictive after removing g.

 

[jigcel]

Shut the fuck up and rot nigger why even make a thread like this

 

[Rigged]

Yes,, this was grossly p-hacked

Nigga wtf no they werent schmidt and hunter are respected how r u gon claim p hacking when u dont know what they are, also they validated across 85 years

and did not replicate "Hunter (1983, 1986) demonstrated this clearly with U.S. Employment Service General Aptitude Test Battery (GATB) validitydata for 5 15 occupations (see also Gutenberg, Arvey, Osburn, & Jeanneret,1983)."

Hunter literally contradicts u low comp jobs 0.23 medium 0.51 high 0.57 another case of u not reading ur own studies this would be like 10 fallacies by now

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This (2024) shows that less complex military jobs had a bigger g-loading that simple military jobs

Yeh bro u dont understand g loading and u resent the same thing i replied to three fucking times

 

[Rigged]

Wrong, if other predictors of jobs performance outperform IQ, then IQ a weak predictor. For example, job specific knowledge tests are more predictive than IQ tests, adding iq tests yields no predictive utility.

Iq tests measure GCA which is broader u fucktard, job specific knowledge tests predicts tasks already learned its useless for checking new problems

IQ = INVALID.

Even paul sacket who critiqued schmidt and hunter says GCA is related to job performance

Standardized tests and subjective specific tests (that have been use to show that learning speed is linear) are also predictive after removing g.

If ur confusing different types of predictors u should do some more research

 

[Rigged]

Shut the fuck up and rot nigger why even make a thread like this

For u to stop being a retard, idk if thats possible tho this could if ur insanely lucky get u +15 iq, thatd put u at 80 the average of a negroid american

 

[Rigged]

What you IQcels even do with all this info jfl

Use it, what do u think we just write it and forget about it

 

[Swarthy Knight]

Use it, what do u think we just write it and forget about it

Use it for what tho. Flex on a Dalit forum? Do you gain monetary value, does it make you feel euphoric, does it help you become slayer, etc..

 

[Rigged]

Use it for what tho. Flex on a Dalit forum? Do you gain monetary value, does it make you feel euphoric, does it help you become slayer, etc..

Increase iq

 

[bubba_ge3]

R

Spoiler: Must Read First

Before any AI accusations come, ill provide pics

AI was only used to translate reformat and rewrite (casually) the original info doesn't come from AI but from a much larger project, also I've only read 60% of the project as only 60% was written by me, the other 40% was written by my partners
View attachment 3400383
View attachment 3400384

Spoiler: Credits (Pls read)

Science Writer 1: RiggedSG
Ethics Writer 2: YBTec
Technology Writer 3: Opbody
Ethics Writer 4: OceDoon

Editor 1: YBTec
Editor 2: OceDoon

QC: RiggedSG

Translation: Google Docs

Repurposed: ChatGPT

Title writer: ChatGPT

Intro/TLDRs: Ollama/LLM

Formats(spoilers): Rigged
Formats(spoilers): Chatgpt

Hello, this was at one point a project of mine and a few friends, not originally for org but i repurposed it to fit here better using ChatGPT, and sadly alot of wording and structure was lost in process, the original document was 4x longer at around 200k characters, sadly the limit is 100k here and to simply repurpose I had to bring it down to 50k

View attachment 3400361

Originally a Russian document translated with DOCS, so any issues presented cant be accounted for
View attachment 3400338

Spoiler: Part I: Foundations of Intelligence

Spoiler: Chapter 1: The Architecture of Intelligence

Spoiler: Lesson 1: Defining Intelligence—A Multidimensional Construct

Introduction
Intelligence is the capacity to acquire, apply, and adapt knowledge and skills to solve problems across diverse contexts. It is not singular but multifaceted, exists as the intersection of neurobiology, psychology, and computational science.

Historical Evolution of Intelligence Theory
Spearman’s g-Factor (1904) introduced the concept of a general intelligence factor, proposing that cognitive abilities are driven by a singular mental energy. This hypothesis was challenged by Thurstone, who argued for primary mental abilities like verbal comprehension, spatial visualization, and numerical reasoning.

Cattell expanded the field by distinguishing fluid intelligence (problem solving and adaptability) from crystallized intelligence (accumulated knowledge). These ideas culminated in the CHC Model, which organizes intelligence hierarchically, integrating both general and specific cognitive domains.

Modern computational theories liken intelligence to machine learning processes, emphasizing hierarchical abstraction and neural optimization. Gardner’s multiple intelligences framework challenged the traditional IQ paradigm by proposing independent intelligences like musical, interpersonal, and kinesthetic abilities.

Theoretical Models Across Disciplines
Neuroscience reveals intelligence as an emergent property of neural network interactions. Psychology examines cognitive and emotional dimensions, while artificial studies provide algorithms simulating learning and adaptation.

Spoiler: Lesson 2: From Neurons to Networks—Connectomics and the Functional Basis of IQ

Neural Architecture and Intelligence
Connectomics maps the brain’s structural and functional connectivity, revealing the networks responsible for cognition. Advances in imaging technologies, such as diffusion tensor imaging (DTI) and functional MRI (fMRI), have allowed researchers to observe how neural pathways underpin intelligence.

Core Brain Networks
The frontoparietal network supports reasoning, working memory, and decision-making. The default mode network governs introspection and creativity. The salience network coordinates attention and switching between tasks. Rich-club hubs integrate these systems, ensuring efficient global communication.

Network Efficiency and Graph Theory
High IQ individuals exhibit more efficient networks, with metrics like degree centrality and clustering coefficients reflecting optimized connectivity. Entropy in neural systems, balanced between order and randomness, enhances adaptability.

Spoiler: Lesson 3: Entropy and Complexity—An Information-Theoretic Perspective

Entropy and Cognitive Dynamics
Entropy measures variability in neural activity, with high entropy supporting creativity and low entropy favoring focus. The brain operates near the edge of chaos, a critical state balancing stability and adaptability.

Complexity as a Cognitive Benchmark
Fractal structures in neural activity reflect hierarchical organization and scalability. Predictive coding minimizes surprise by refining mental models, aligning with the free energy principle.

Practical Applications of Complexity Theory
Understanding entropy and complexity informs the design of adaptive systems and neural training protocols, enhancing cognitive flexibility and creativity.

Spoiler: Lesson 4: The Role of Neural Plasticity in Intelligence

Mechanisms of Plasticity
Synaptic plasticity, including long term potentiation (LTP) and depression (LTD), facilitates learning and memory. Structural plasticity involves dendritic growth and synaptogenesis.

Lifespan Adaptability
Plasticity declines with age but can be maintained through interventions like cognitive training and physical exercise. Neurogenesis in the hippocampus supports memory and pattern separation.

Molecular Influences
Molecules like BDNF and CREB regulate plasticity, with environmental factors such as stress, diet, and enrichment shaping expression.

Spoiler: Lesson 5: The Energy Dynamics of Intelligence

Brain Metabolism
Neurons consume large amounts of energy, primarily derived from glucose. Higher IQ brains optimize energy usage, as evidenced by localized glucose metabolism.

Mitochondrial Efficiency
Mitochondria power neural activity. Enhancers like NAD+ precursors and CoQ10 improve energy availability, supporting cognitive performance.

Energy Optimization Strategies
Dietary interventions, such as ketogenic diets and intermittent fasting, enhance mitochondrial efficiency and reduce oxidative stress.

Spoiler: Lesson 6: Genetics and Heritability of Intelligence

Polygenic Contributions
Intelligence is influenced by many genes with small effects. GWAS studies identify loci associated with cognitive traits, including COMT, BDNF, and APOE.

Epigenetic Modulation
Environmental factors alter gene expression, with implications for learning and adaptability. Techniques like CRISPR enable potential genetic enhancements.

Transgenerational Effects
Epigenetic changes from stress or enrichment in one generation can influence the cognitive traits of descendants.

Spoiler: Lesson 7: The Cognitive Impacts of Emotional Regulation

Neurobiology of Emotion
The prefrontal cortex, amygdala, and anterior cingulate cortex mediate emotional control. Emotional regulation strategies, such as cognitive reappraisal and mindfulness, enhance decision-making and resilience.

Stress and Performance
Optimal stress levels maximize focus and problem solving, following the Yerkes Dodson law. Overexposure to stress impairs cognitive performance.

Tools for Emotional Regulation
Biofeedback and neurofeedback systems train users in emotional control, improving cognitive flexibility and stress resilience.

Spoiler: Part II: Enhancing Neural Capacity

Spoiler: Chapter 2: Neurobiological Foundations

Spoiler: Lesson 1: The Molecular Basis of Intelligence

Introduction
Understanding the molecular basis of intelligence involves exploring the biochemical processes that underpin cognition. This includes synaptic activity, neurotransmitter systems, and the roles of specific neurotrophic factors.

Neurotransmitters and Cognition
Dopamine: Critical for reward processing, motivation, and executive function. Dopaminergic pathways in the prefrontal cortex influence working memory and decision-making.
Glutamate: The primary excitatory neurotransmitter, essential for synaptic plasticity and long-term potentiation (LTP).
Serotonin: Regulates mood, social cognition, and memory consolidation.

Neurotrophic Factors
Brain Derived Neurotrophic Factor (BDNF): Promotes synaptic growth and plasticity, crucial for learning and memory.
Nerve Growth Factor (NGF): Supports survival and differentiation of neurons, particularly in the peripheral nervous system.
Vascular Endothelial Growth Factor (VEGF): Enhances angiogenesis in the brain, supporting oxygen and nutrient delivery.

Spoiler: Lesson 2: Genetic Contributions to Cognitive Capacity

Polygenic Inheritance
Cognitive traits are influenced by numerous genes with small additive effects. Genome wide association studies (GWAS) have identified loci linked to IQ and educational attainment.
Key Genes
BDNF: Regulates synaptic plasticity and resilience to stress.
COMT: Modulates dopamine metabolism, influencing executive function.
APOE: Associated with memory and age-related cognitive decline.

Epigenetic Modulation
Environmental factors like diet, stress, and learning experiences can modify gene expression through mechanisms such as DNA methylation and histone acetylation.

Spoiler: Lesson 3: Neural Plasticity and Adaptability

Mechanisms of Plasticity
Long Term Potentiation (LTP): Strengthens synaptic connections through repetitive stimulation, enhancing learning.
Long Term Depression (LTD): Reduces synaptic strength, allowing for neural pruning and efficiency.
Structural Plasticity: Involves dendritic spine growth and synaptogenesis, critical for adapting to new information.

Applications of Plasticity
Cognitive training enhances neural plasticity in regions like the prefrontal cortex.
Exercise induced BDNF release promotes hippocampal neurogenesis, improving memory.

Spoiler: Lesson 4: Neural Oscillations and Cognitive States

Introduction
Neurons communicate via electrical signals that oscillate at different frequencies, supporting various cognitive functions.

Key Frequency Bands
Delta (1-4 Hz): Associated with deep sleep and memory consolidation.
Theta (4-8 Hz): Facilitates working memory and attention.
Alpha (8-12 Hz): Linked to relaxed alertness and focus.
Gamma (30-100 Hz): Integrates information across brain regions, critical for higher-order processing.

Functional Implications
Theta-gamma coupling in the hippocampus underpins episodic memory formation.
Disruptions in oscillatory activity are implicated in disorders like schizophrenia and ADHD.

Spoiler: Lesson 5: The Role of Myelination in Processing Speed

Myelin and Neural Efficiency
Myelin sheaths insulate axons, increasing the speed of signal transmission. Efficient myelination enhances processing speed and reaction times.

Myelination Across the Lifespan
Myelination peaks in early adulthood but continues to adapt based on experience and learning. Cognitive decline in aging is partly attributed to demyelination.

Interventions to Support Myelination
Nutritional support: Omega-3 fatty acids and choline-rich diets promote myelin health.
Physical activity and skill learning enhance oligodendrocyte activity, maintaining myelination.

Spoiler: Lesson 6: Neural Energy Dynamics and Cognitive Performance

Brain Metabolism
The brain, while constituting only 2% of body weight, consumes 20% of the body’s energy. Glucose is the primary fuel, but ketones provide an alternative energy source during fasting or ketogenic states.

Mitochondrial Efficiency
Mitochondria generate ATP, the energy currency of cells. Dysfunctional mitochondria impair cognitive function and contribute to neurodegenerative diseases.

Enhancing Energy Dynamics
Dietary interventions, such as intermittent fasting, improve mitochondrial efficiency. Nootropic compounds like acetyl-L-carnitine support energy metabolism.

Spoiler: Lesson 7: The Blood-Brain Barrier and Cognitive Protection

Structure and Function
The blood-brain barrier (BBB) protects the brain from toxins while allowing essential nutrients to pass. It maintains the brain’s microenvironment, crucial for neural function.

BBB Integrity and Cognitive Health
Disruption of the BBB is linked to neuroinflammatory conditions and cognitive decline. Lifestyle factors like exercise and dietary antioxidants support BBB integrity.

Spoiler: Lesson 8: Future Directions in Neurobiology

Emerging Technologies
Optogenetics allows precise control of neural activity using light-sensitive proteins.
CRISPR-based interventions hold potential for correcting genetic mutations associated with cognitive deficits.

Spoiler: Chapter 3: Pharmacological Pathways to Intelligence

Spoiler: Lesson 1: Introduction to Nootropics

Definition and
Nootropics, or cognitive enhancers, are substances that improve mental functions such as memory, creativity, focus, and executive function without causing significant side effects.

Categories of Nootropics
Natural compounds: Herbal extracts like Ginkgo biloba and Bacopa monnieri.
Synthetic compounds: Piracetam, Modafinil, and Ampakines.
Pharmaceuticals: Drugs developed for conditions like ADHD, with off-label use for cognitive enhancement.

Mechanisms of Action
Increasing neurotransmitter availability (acetylcholine, dopamine).
Enhancing synaptic plasticity and neuroprotection.

Spoiler: Lesson 2: Dopaminergic and Serotonergic Modulation

Dopamine Pathways
The mesolimbic and mesocortical pathways regulate motivation and working memory. Drugs like Modafinil and L-DOPA modulate dopamine levels to enhance executive function.

Serotonin’s Role in Cognition
Serotonin affects mood regulation and memory formation. SSRIs and serotonin precursors (5-HTP) may indirectly influence cognitive performance.

Spoiler: Lesson 3: Enhancing Synaptic Plasticity with Ampakines

Mechanism of Action
Ampakines modulate AMPA receptors to facilitate long term potentiation (LTP). This enhances learning and memory formation.

Applications
Experimental drugs like CX717 show promise in improving attention and problem solving skills.

Safety and Limitations
Ampakines are still in research phases, with limited understanding of long-term effects.

Spoiler: Lesson 4: Cholinergic Pathways and Memory Enhancement

The Role of Acetylcholine
Acetylcholine is critical for attention and memory consolidation. Cholinergic drugs like Donepezil and Galantamine inhibit acetylcholinesterase, increasing acetylcholine availability.

Supplements and Precursors
Alpha-GPC and Citicoline are effective precursors for boosting acetylcholine synthesis.

Spoiler: Lesson 5: Modulating Glutamate and GABA Systems

Glutamate for Excitatory Activity
Glutamate supports synaptic plasticity and cognitive flexibility. Drugs like Memantine target NMDA receptors to prevent excitotoxicity while enhancing learning.

GABA for Stress Reduction
GABAergic compounds like Phenibut and Gabapentin reduce anxiety, promoting focus in high-stress environments.

Spoiler: Lesson 6: Neurogenesis and Cognitive Enhancers

Promoting Neurogenesis
Compounds like NSI-189 and Lions Mane Mushroom stimulate hippocampal neurogenesis, improving memory and mood.

Exercise and Neurogenesis
Aerobic activity boosts neurogenesis-related pathways, synergizing with pharmacological approaches.

Spoiler: Lesson 7: Emerging Pharmacological Interventions

Microdosing Psychedelics
Low doses of LSD or Psilocybin show promise for enhancing creativity and emotional flexibility.

Synthetic Compounds
Experimental drugs targeting the CREB-BDNF pathway aim to amplify learning capabilities.

Spoiler: Lesson 8: Risks and Ethical Considerations

Short Term Risks
Side effects such as dependence, tolerance, and unintended cognitive trade-offs.

Long Term Implications
Ethical concerns around fairness and accessibility, especially in competitive academic or professional settings.

Spoiler: Chapter 4: Advanced Neurotechnology

Spoiler: Lesson 1: Brain-Computer Interfaces (BCIs)

Definition and Mechanisms
BCIs enable direct communication between the brain and external devices, translating neural signals into actionable commands for machines or software.

Applications in Cognitive Enhancement
Restorative BCIs: Assist individuals with paralysis or neurodegenerative conditions.
Augmentative BCIs: Enhance memory retention, learning speed, and decision-making in healthy individuals.

Technological Challenges
Signal noise and resolution: Improving the accuracy of neural signal interpretation.
Invasiveness: Balancing efficacy with safety in invasive versus non-invasive BCIs.

Spoiler: Lesson 2: Non-Invasive Brain Stimulation Techniques

Transcranial Magnetic Stimulation (TMS)
TMS delivers magnetic pulses to stimulate specific brain regions, enhancing cognitive functions like attention and memory.
Clinical Uses: Approved for depression, with off-label applications for cognitive enhancement.

Transcranial Direct Current Stimulation (tDCS)
tDCS applies a low electrical current to modulate neuronal excitability. Research suggests benefits in problem solving and creativity.

Spoiler: Lesson 3: Neural Implants for Memory Augmentation

Advancements in Neural Implants
Devices like hippocampal prosthetics aim to restore or enhance memory by mimicking neural activity patterns.

Key Projects
The DARPA RAM (Restoring Active Memory) program develops implants to assist individuals with traumatic brain injuries.

Spoiler: Lesson 4: Neurofeedback Systems

Real Time Cognitive Training
Neurofeedback provides individuals with live data on their brain activity, enabling self regulation of attention and emotional states.

Applications
Improving focus in ADHD patients.
Enhancing peak performance in athletes and professionals.

Spoiler: Lesson 5: Optogenetics and Precision Neural Control

What is Optogenetics?
Optogenetics uses light-sensitive proteins to control neural activity with high precision.

Applications in Research
Mapping brain circuits to understand memory, learning, and emotion.
Experimental treatments for conditions like Parkinson’s and epilepsy.

Spoiler: Lesson 6: Wearable Neurotechnology

Emerging Devices
Headsets that monitor EEG activity to optimize focus and relaxation.
Sleep enhancement devices that improve memory consolidation.

Consumer Applications
Wearables designed for gamers, executives, and students aiming to boost cognitive performance.

Spoiler: Lesson 7: The Future of Neural Interfaces

Hybrid Systems
Combining BCIs with AI for real-time decision support and complex problem-solving.

Brain to Brain Communication
Research explores direct neural communication between individuals, enabling collaborative cognition.

Potential Risks
Dependence on external systems.
Unintended consequences of altering neural activity patterns.

Spoiler: Lesson 8: Ethical and Societal Implications

Equity in Access
Ensuring neurotechnological advancements are available to all, preventing cognitive inequality.

Privacy and Security
Protecting neural data from misuse, including unauthorized access or hacking.

Spoiler: Chapter 5: Neurogenomics and Epigenetics

Spoiler: Lesson 1: Introduction to Neurogenomics

The Scope of Neurogenomics
Neurogenomics studies the relationship between genes and brain function, aiming to understand how genetic variations influence cognitive abilities.

The Genetic Basis of Intelligence
Polygenic inheritance: Cognitive traits are influenced by hundreds of genetic variants, each contributing a small effect.
Major candidate genes: BDNF (neuroplasticity), COMT (dopamine metabolism), APOE (memory and aging).

Spoiler: Lesson 2: The Role of Epigenetics in Cognition

Epigenetic Mechanisms
DNA methylation: Silences or activates gene expression without altering the DNA sequence.
Histone modification: Changes chromatin structure, affecting gene accessibility.
Non-coding RNAs: Regulate post-transcriptional gene expression.

Environmental Influences
Nutrition: Diets rich in omega-3s and antioxidants promote favorable epigenetic profiles.
Stress: Chronic stress induces methylation changes, suppressing neuroplasticity genes.

Spoiler: Lesson 3: Gene-Environment Interactions

Examples of Gene Environment Interplay
BDNF Val66Met polymorphism: Influences how individuals respond to stress and learning environments.
COMT variants: Modulate executive function under varying levels of cognitive load.

Educational Interventions
Early enrichment programs can amplify genetic predispositions toward high intelligence by influencing epigenetic states.

Spoiler: Lesson 4: Tools and Techniques in Neurogenomics

CRISPR-Cas9 Gene Editing
Applications: Editing genes linked to cognitive deficits or enhancing plasticity pathways.
Challenges: Off-target effects and ethical concerns.

Single Cell Sequencing
Unveils the diversity of gene expression profiles across individual neurons, offering insights into brain heterogeneity.

Spoiler: Lesson 5: Neuroepigenetics Across the Lifespan

Critical Periods in Development
Early childhood represents a window of heightened epigenetic sensitivity, where environmental factors exert lasting impacts on cognition.

Aging and Cognitive Decline
Age related changes in methylation patterns contribute to cognitive deficits. Interventions like caloric restriction can mitigate epigenetic aging.

Spoiler: Lesson 6: Epigenetic Therapeutics for Cognitive Enhancement

Histone Deacetylase Inhibitors (HDACis)
These compounds enhance memory and learning in preclinical studies by promoting gene expression linked to plasticity.

Potential Therapies
Drugs targeting the BDNF pathway to boost resilience against cognitive decline.

Spoiler: Lesson 7: Transgenerational Epigenetic Inheritance

Mechanisms of Inheritance
Epigenetic marks influenced by environmental factors, such as stress or famine, can be passed to subsequent generations.

Implications for Cognitive Traits
Studies suggest that enriched or impoverished environments may affect the cognitive potential of descendants through epigenetic transmission.

Spoiler: Part III: Cognitive Optimization Protocols

Spoiler: Chapter 6: Lifestyle Design for Intelligence

Spoiler: Lesson 1: Sleep Optimization and Intelligence

Introduction
Intelligence is not a static attribute; it is a dynamic interplay of genetic predisposition, environmental factors, and lifestyle choices. The goal of this chapter is to provide an exhaustive exploration of how sleep, diet, exercise, and stress management can optimize intelligence by enhancing neuroplasticity, energy efficiency, and long-term brain health.

The Role of Sleep in Cognitive Function
- REM sleep supports emotional regulation, divergent thinking, and creativity by integrating neural networks.
- Deep sleep facilitates memory consolidation, neural repair, and glymphatic clearance of waste products.

Neurochemical Pathways During Sleep
- GABA and melatonin regulate sleep onset and transitions between sleep stages.
- Orexin and adenosine influence arousal and sleep debt mechanisms.

Sleep Disorders and Cognitive Decline
- Chronic sleep deprivation leads to beta-amyloid accumulation, increasing Alzheimer’s risk.
- Insomnia impairs synaptic plasticity, reducing learning efficiency.

Strategies for Sleep Enhancement
- Personalized sleep tracking with wearable devices (WHOOP, Oura Ring).
- Cognitive-behavioral therapy for insomnia (CBT-I) as a non-pharmacological intervention.
- Advanced pharmacological options: Suvorexant for regulating sleep-wake cycles.

Spoiler: Lesson 2: Nutrition and Cognitive Optimization

The Biochemistry of Brain Energy
- Glucose metabolism supports synaptic activity, while ketones provide neuroprotective effects.
- The role of mitochondria in ATP production and cognitive endurance.

Neuroprotective Nutrients
- Omega-3 fatty acids enhance synaptic plasticity and reduce inflammation.
- Flavonoids in berries and dark chocolate support angiogenesis and memory formation.

Microbiota and the Gut-Brain Axis
- Specific probiotic strains, such as Lactobacillus rhamnosus, influence GABA production.
- High-fiber diets reduce systemic inflammation, improving cognitive resilience.

Practical Dietary Frameworks
- Designing a brain optimized meal plan with nutrient timing (time restricted eating).
- Exploring culturally specific dietary adaptations for cognitive benefits.

Spoiler: Lesson 3: Exercise as a Cognitive Enhancer

The Neuroscience of Movement
- Aerobic exercise increases hippocampal volume via BDNF mediated neurogenesis.
- Resistance training improves executive function through myokine secretion.

Synergistic Effects of Exercise
- Combining physical activity with cognitive tasks (dual task training) amplifies neural efficiency.
- High altitude training and oxygenation’s impact on cerebral blood flow.

Emerging Interventions
- Virtual reality (VR) environments for immersive physical and cognitive training.
- Electrical stimulation devices (EMS) to enhance motor cognitive integration.

Spoiler: Lesson 4: Stress Management and Neural Resilience

The Cortisol Intelligence Link
- Chronic stress disrupts connectivity between the amygdala and prefrontal cortex, impairing decision-making.
- Acute stress facilitates adaptive learning under pressure through catecholamine release.

Techniques for Resilience Building
- Cold exposure and its hormetic effects on mitochondrial biogenesis.
- Mindfulness apps (Calm, Headspace) and their neural correlates in fMRI studies.

Advanced Stress Modulation
- Neurofeedback protocols for autonomic control (HRV biofeedback).
- Pharmacological interventions targeting the HPA axis.

Spoiler: Lesson 5: Environmental and Social Influences on Intelligence

Cognitive Ecology
- The impact of noise pollution and environmental toxins (lead, PM2.5) on cognitive health.
- Designing workspaces that maximize focus and creativity through biophilic design.

Social Networks and Cognitive Growth
- The role of mentorship and collaborative learning in accelerating problem-solving skills.
- Collective intelligence: Group dynamics and their impact on individual IQ.

Spoiler: Lesson 6: Leveraging Technology for Lifestyle Optimization

Wearable and Embedded Devices
- EEG-based neurotech for real-time focus monitoring.
- Personalized AI coaching systems for optimizing daily routines.

Neurostimulation
- Transcranial direct current stimulation (tDCS) for improving task-switching abilities.
- Home use TMS devices for mood and memory enhancement.

Spoiler: Lesson 7: Designing a Personalized Protocol

Step by Step Framework
1. Assess baseline metrics: Cognitive assessments, sleep data, and biomarker panels.
2. Implement modular interventions: Begin with sleep optimization and layer in dietary and exercise adjustments.
3. Iterate and adapt: Regularly update protocols based on performance metrics.

Case Studies
- High performing individuals (e.g., athletes, executives) and their tailored protocols.
- Longitudinal studies on lifestyle interventions and cognitive outcomes.

Spoiler: Chapter 7: Cognitive Training Methodologies

Spoiler: Lesson 1: Spaced Repetition and Interleaving

Introduction
Cognitive training involves systematic, evidence based techniques to enhance specific mental abilities such as memory, attention, problem solving, and executive function. This chapter delves into the neuroscience underlying these methods and provides strategies for implementing cognitive training.

The Science Behind Memory Retention
- Spaced repetition optimizes learning by reinforcing material at increasing intervals, leveraging the spacing effect.
- Interleaving mixes topics or skills within a single session, enhancing problem-solving by requiring flexible cognitive shifts.

Practical Implementation
- Tools such as Anki and SuperMemo for designing personalized spaced repetition schedules.
- Integrating interleaving into educational curriculums and real-world applications.

Neurobiological Insights
- The hippocampus and prefrontal cortex work in tandem during spaced repetition to strengthen synaptic connections.
- Dopaminergic reinforcement in interleaved learning supports cognitive adaptability.

Spoiler: Lesson 2: Enhancing Working Memory

The Role of Working Memory in Intelligence
- Working memory is central to fluid intelligence, enabling temporary information storage and manipulation.
- Enhanced working memory capacity correlates with higher IQ scores and problem-solving skills.

Evidence-Based Training Techniques
- Dual-N-back training: Engages auditory and visual memory circuits to improve executive function.
- Chunking strategies: Grouping information into meaningful patterns to maximize memory efficiency.

Neural Mechanisms
- Prefrontal cortex activation during training enhances synaptic plasticity.
- Theta-gamma coupling in the hippocampus improves working memory encoding.

Spoiler: Lesson 3: Neurofeedback and Attention Control

What is Neurofeedback?
- Neurofeedback provides real-time brain activity data, allowing users to self-regulate their mental states.
- Applications range from ADHD management to peak performance enhancement.

Protocols for Attention Training
- EEG-based neurofeedback for enhancing sustained focus.
- Combining mindfulness meditation with neurofeedback to optimize task-specific attention.

Spoiler: Lesson 4: Gamification in Cognitive Training

The Role of Motivation in Cognitive Enhancement
- Gamification introduces elements like rewards, progress tracking, and challenges to sustain engagement.

Examples of Gamified Platforms
- Lumosity and CogniFit: Evidence-based games targeting various cognitive domains.
- Real-world simulation games for problem-solving and decision-making under pressure.

Spoiler: Lesson 5: Advanced Techniques in Cognitive Training

Brain-Computer Interfaces (BCIs)
- BCIs detect neural activity to provide tailored cognitive training feedback.
- Emerging applications in rehabilitation and high-performance learning environments.

Virtual and Augmented Reality
- Immersive environments for experiential learning and cognitive task simulations.
- VR systems for multitasking and spatial memory training.

Spoiler: Lesson 6: Integrating Cognitive Training into Daily Life

Designing a Comprehensive Training Protocol
1. Assess baseline cognitive performance using tools like WAIS-IV or computerized cognitive batteries.
2. Combine training methodologies: Interleave memory, attention, and problem-solving exercises for maximum synergy.
3. Monitor progress: Use apps and neurofeedback devices to track improvements.

Applications in Professional Fields
- Military training for decision-making under stress.
- Corporate settings for enhancing productivity and teamwork.

Spoiler: Chapter 8: Leveraging the Gut-Brain Axis

Spoiler: Lesson 1: The Microbiome's Role in Neurotransmitter Synthesis

Introduction
The gut-brain axis is a bidirectional communication network linking the gastrointestinal system and the central nervous system. Emerging research highlights the role of the gut microbiota in modulating cognitive functions such as memory, mood, and decision-making. This chapter explores the intricate mechanisms of gut-brain interactions, evidence-based interventions, and practical applications for optimizing cognitive performance.

Mechanisms of Influence
- Gut bacteria produce neurotransmitters such as serotonin, dopamine, and GABA, directly impacting brain function.
- The vagus nerve serves as a conduit for microbial metabolites to influence neural activity.

Key Microbial Strains
- Lactobacillus rhamnosus: Enhances GABAergic signaling, reducing anxiety.
- Bifidobacterium longum: Associated with improved memory and stress resilience.

Clinical Implications
- Dysbiosis (microbial imbalance) is linked to cognitive impairments in conditions like depression, anxiety, and Parkinson’s disease.
- Restoring microbial balance through dietary and probiotic interventions improves cognitive outcomes.

Spoiler: Lesson 2: Probiotic and Prebiotic Interventions

Probiotics for Cognitive Health
- Probiotic supplementation enhances gut-brain signaling and reduces neuroinflammation.
- Key strains: Lactobacillus helveticus, Bifidobacterium infantis, and Saccharomyces boulardii.

Prebiotic Compounds
- Prebiotics, such as inulin and fructooligosaccharides, stimulate beneficial bacterial growth.
- Foods like garlic, onions, and bananas provide natural prebiotic sources.

Emerging Psychobiotics
- Psychobiotics are probiotics specifically targeting mental health and cognitive enhancement.
- Evidence shows psychobiotics reduce stress and improve mood through the hypothalamic-pituitary-adrenal (HPA) axis.

Spoiler: Lesson 3: The Gut-Inflammation-Cognition Connection

Inflammatory Pathways
- Chronic systemic inflammation, driven by an imbalanced gut microbiota, impairs neurogenesis and synaptic plasticity.
- Pro inflammatory cytokines (IL-6, TNF-α) disrupt blood brain barrier integrity, leading to cognitive decline.

Dietary Strategies for Reducing Inflammation
- Anti inflammatory diets rich in omega-3s, polyphenols, and fiber mitigate neuroinflammation.
- Fermented foods such as kimchi and yogurt support gut health while reducing inflammatory markers.

Spoiler: Lesson 4: Gut-Brain Axis and Stress Resilience

The HPA Axis and Microbial Modulation
- The microbiota influences cortisol release through gut-derived metabolites.
- Balancing the gut microbiota reduces the negative cognitive impacts of chronic stress.

Practical Stress Mitigation Strategies
- Combining prebiotic supplementation with mindfulness meditation enhances stress resilience.
- Regular consumption of fermented foods improves microbiota diversity, supporting adaptive stress responses.

Spoiler: Lesson 5: Technological and Future Innovations

Microbiome Profiling
- Advances in microbiome sequencing allow personalized interventions based on individual microbial compositions.
- Tools such as uBiome and Viome provide actionable insights for optimizing gut health.

Fecal Microbiota Transplantation (FMT)
- Experimental use of FMT shows promise for treating cognitive impairments related to dysbiosis.
- Ethical and safety considerations remain critical for widespread adoption.

Synthetic Biology in Microbiota Engineering
- Genetically engineered probiotics designed to produce targeted neurotransmitters are on the horizon.
- Potential applications include personalized psychobiotics tailored for specific cognitive goals.

Spoiler: Lesson 6: Integrating Gut-Brain Optimization into Daily Life

Practical Steps
1. Maintain a balanced diet: Emphasize high-fiber, fermented, and anti-inflammatory foods.
2. Monitor gut health: Use at-home microbiome testing kits to track progress.
3. Implement stress management techniques: Combine dietary strategies with practices like yoga and biofeedback.

Case Studies
- Real world examples of individuals and athletes using gut-brain optimization to enhance focus, resilience, and performance.
- Clinical trials showing improved cognition with targeted probiotic interventions.

Spoiler: Part IV: Theoretical Frontiers and Emerging Paradigms

Spoiler: Chapter 9: Quantum Cognition

Spoiler: Lesson 1: Theoretical Foundations of Quantum Cognition

Introduction
Quantum cognition offers a groundbreaking framework for understanding mental processes, decision-making, and memory through the principles of quantum mechanics. While traditional cognitive models assume deterministic, linear systems, quantum cognition introduces probabilistic, non-linear interactions, capturing the nuances of human thought. This chapter explores the theoretical underpinnings, experimental evidence, and future applications of quantum cognition in neuroscience and psychology.

Classical vs. Quantum Perspectives
- Classical models rely on fixed probabilities and deterministic pathways, often failing to capture paradoxical decision-making behaviors.
- Quantum models introduce superposition and entanglement, enabling a richer, more flexible representation of cognitive states.

Quantum Probability Theory
- Decision-making is modeled as a quantum state collapse, where competing cognitive states coexist in superposition until a choice is made.
- Explains phenomena like the conjunction fallacy and preference reversals that deviate from classical rationality.

Applications in Human Behavior
- Quantum models provide insights into intuition, creativity, and emotional responses, offering a robust alternative to purely logical frameworks.

Spoiler: Lesson 2: Neural Correlates of Quantum Processes

Entanglement in Neural Networks
- Large-scale neural synchrony resembles quantum entanglement, where distant brain regions exhibit correlated activity without direct connections.
- Functional magnetic resonance imaging (fMRI) and EEG studies reveal patterns consistent with entangled cognitive processes.

Microtubules as Quantum Processors
- The Penrose-Hameroff Orch-OR theory suggests that microtubules within neurons perform quantum computations, influencing perception and decision-making.
- Evidence from quantum coherence in microtubules supports their role in neural information processing.

Spoiler: Lesson 3: Experimental Evidence for Quantum Cognition

Behavioral Studies
- Experiments reveal interference patterns in decision-making tasks, analogous to wave-particle duality in quantum mechanics.
- Reaction time distributions align with quantum probability models, offering predictive power for complex cognitive tasks.

Neurobiological Insights
- Advanced imaging techniques demonstrate coherence and decoherence patterns in brain activity during decision-making and memory retrieval.
- Quantum models account for the brain's ability to process ambiguous or contradictory information simultaneously.

Spoiler: Lesson 4: Quantum Computing and Cognitive Science

Quantum Computing as a Cognitive Model
- Quantum algorithms simulate human problem-solving, offering analogs for brain functions like pattern recognition and optimization.
- Grover’s algorithm parallels human search strategies in memory retrieval.

Applications in Neuroscience
- Quantum machine learning enhances data analysis in brain imaging and genetics, uncovering hidden patterns in cognitive disorders.
- Development of quantum-inspired neural networks to emulate probabilistic and parallel processing.

Spoiler: Lesson 5: Implications for Artificial Intelligence

Quantum-Enhanced AI
- Quantum cognition inspires AI architectures capable of handling uncertainty and ambiguity, mimicking human intuition.
- Applications in dynamic decision-making, such as autonomous systems and adaptive learning platforms.

Human-AI Collaboration
- Integrating quantum cognitive models into AI improves compatibility with human thought processes, enabling seamless interaction.
- Real-world applications include advanced recommendation systems and strategic decision support.

Spoiler: Lesson 6: Philosophical and Ethical Considerations

Redefining Rationality
- Quantum cognition challenges classical notions of rationality, emphasizing context-dependent and non-linear thought processes.
- Raises questions about free will and determinism in light of probabilistic mental states.

Ethical Implications
- Quantum-based interventions in cognition, such as neurostimulation or AI-assisted decision-making, pose risks of manipulation and loss of autonomy.
- Ensuring equitable access to quantum technologies is crucial to prevent cognitive stratification.

Spoiler: Lesson 7: Future Directions in Quantum Cognition

Technological Innovations
- Quantum-enhanced imaging tools for real-time analysis of neural coherence and decision-making processes.
- Development of hybrid systems combining quantum processors with biological neural networks.

Theoretical Advancements
- Exploring the role of entanglement and superposition in group dynamics and collective intelligence.
- Refining quantum models to integrate emotional and subconscious influences on cognition.

Spoiler: Chapter 10: Deleted

N/A

Spoiler: Chapter 11: Collective Intelligence and Network Theory

Spoiler: Lesson 1: Principles of Collective Intelligence

Introduction
Collective intelligence arises when individuals collaborate, pooling their cognitive resources to solve complex problems. Rooted in network theory, this phenomenon demonstrates how distributed systems outperform individual agents by leveraging diversity, redundancy, and connectivity. This chapter explores the science of collective intelligence, its applications, and its implications for the future of human collaboration.

Defining Collective Intelligence
- The emergent property of group cognition, where the whole is greater than the sum of its parts.
- Found in biological systems (ant colonies, bee swarms) and human social networks.

Core Mechanisms
- Diversity: Diverse perspectives enhance problem-solving by expanding the solution space.
- Decentralization: Distributing decision-making prevents bottlenecks and enhances adaptability.
- Aggregation: Synthesizing individual contributions into coherent group outputs.

Spoiler: Lesson 2: Network Theory in Collective Intelligence

Understanding Network Structures
- Nodes and edges: Individuals and their connections form the basis of social networks.
- Centrality metrics (betweenness, degree) identify key influencers within networks.

Small World Networks
- Combining local clustering and global connectivity enhances information flow and innovation.
- Real-world examples include scientific collaborations and online communities.

Scale Free Networks
- Power law distributions ensure robustness against random failures while maintaining vulnerability to targeted attacks.
- Applications in understanding resilience and fragility in collective systems.

Spoiler: Lesson 3: Enhancing Group Dynamics for Problem Solving

Optimizing Collaboration
- Psychological safety: Encouraging open communication without fear of judgment enhances creativity.
- Moderating dominance: Ensuring balanced participation prevents groupthink.

Digital Platforms for Collective Intelligence
- Crowdsourcing platforms like Kaggle and Foldit harness distributed expertise for scientific discovery.
- Blockchain based systems ensure transparency and trust in decentralized collaborations.

Spoiler: Lesson 4: Applications in Global Challenges

Climate Change and Resource Management
- Leveraging collective intelligence to model complex systems and design sustainable policies.
- Examples include citizen science initiatives and global think tanks.

Disaster Response and Crisis Management
- Real-time data aggregation from social media and IoT devices enables adaptive responses.

Spoiler: Lesson 5: Collective Intelligence and Artificial Systems

Swarm Intelligence in Robotics
- Algorithms inspired by biological swarms enable decentralized decision-making in autonomous systems.
- Applications range from search-and-rescue operations to industrial automation.

Spoiler: Lesson 6: Ethical and Philosophical Considerations

Equity in Access
- Addressing digital divides to ensure equitable participation in collective intelligence platforms.
- Ensuring inclusivity in global decision-making processes.

Risks of Manipulation
- Protecting against misinformation and coordinated attacks on collective decision-making systems.
- Developing robust systems to identify and counteract bad actors.

Spoiler: Part V: Practical Applications and Ethical Considerations

Spoiler: Chapter 12: Case Studies in Cognitive Enhancement

Spoiler: Lesson 1: Pharmacological Interventions in Practice

Introduction
Cognitive enhancement encompasses a wide range of interventions, from pharmacological approaches and neurotechnology to behavioral strategies and lifestyle modifications. This chapter examines real-world case studies, highlighting successes, limitations, and lessons learned. By analyzing these examples, we can better understand the practical applications of cognitive enhancement and chart a path forward for future innovations.

Case Study 1: Modafinil in Cognitive Performance

- Context: Use of Modafinil among professionals and students for improving focus and wakefulness.
- Findings: A review by the University of Oxford indicates that Modafinil enhances cognition, particularly in tasks requiring higher cognitive functions, with more pronounced effects under sleep-deprived conditions. Study
- Challenges: Ethical concerns regarding off-label use and the potential for dependency.

Case Study 2: Ritalin and Adderall in Academic Settings

- Context: Widespread use of ADHD medications by non-prescribed users in competitive environments.
- Findings: Research from Brown University suggests that these stimulants do not improve cognition in healthy individuals and may negatively affect performance. Study
- Challenges: Side effects, long-term safety concerns, and unequal access.

Case Study 3: Nootropic Supplements in Aging Populations

- Context: Use of nootropics such as Ginkgo biloba and Bacopa monnieri in older adults.
- Findings: A study in the British Journal of Nutrition reviews the effects of longterm nutraceutical and dietary supplement use on cognition in the elderly, indicating varying results. Study
- Challenges: Variability in supplement quality and inconsistent clinical evidence.

Spoiler: Lesson 2 - Neurotechnology in Real-World Applications

Case Study 1: Transcranial Magnetic Stimulation (TMS) in Depression

- Context: TMS as an FDA-approved treatment for major depressive disorder.
- Findings: A study from Stanford University reports that a new form of TMS brought rapid remission to almost 80% of participants with severe depression. Study
- Challenges: High cost, time-intensive protocols, and limited access in rural areas.

Case Study 2: Brain-Computer Interfaces (BCIs) for Rehabilitation

- Context: Use of BCIs in restoring communication for individuals with paralysis.
- Findings: Recent studies highlight the potential of BCIs in neurorehabilitation, particularly for individuals with conditions such as spinal cord injury and stroke. Study
- Challenges: Invasiveness of some devices and the need for extensive training.

Case Study 3: Neurofeedback in ADHD Management

- Context: EEG-based neurofeedback systems for improving attention and self-regulation.
- Findings: Research indicates that neurofeedback may be effective in treating ADHD, though it is often recommended as part of a comprehensive treatment plan. Study
- Challenges: High variability in outcomes and reliance on trained practitioners.

Spoiler: Lesson 3 - Behavioral and Lifestyle Interventions

Case Study 1: Sleep Optimization for Professional Athletes

- Context: Implementation of personalized sleep protocols for enhanced performance.
- Findings: A systematic review in Sports Medicine - Open discusses the impact of sleep interventions on athletic performance, emphasizing the importance of sleep for recovery and performance. Study
- Challenges: Adherence to protocols during travel and high-pressure situations.

Case Study 2: Exercise and Cognitive Training in Seniors

- Context: Combining aerobic exercise with dual-task cognitive training in older adults.
- Findings: A study published in JAMA Network Open found that combining exercise with cognitive training led to significant improvements in cognitive function among older adults with mild cognitive impairment. Study
- Challenges: Sustained motivation and accessibility for diverse populations.

Case Study 3: Meditation and Stress Management in Corporate Settings

- Context: Mindfulness training programs in high-stress industries (finance, healthcare).
- Findings: A meta-analysis in Mindfulness journal indicates that mindfulness-based programs in the workplace can reduce stress and improve psychological wellbeing. Study
- Challenges: Scalability and maintaining engagement over time.

Spoiler: Lesson 4: Lessons Learned and Future Directions

Successes
- Demonstrated efficacy of targeted interventions in specific populations (ADHD, aging adults).
- Synergistic effects of combining pharmacological, technological, and behavioral approaches.

Limitations
- Variability in outcomes due to genetic, environmental, and individual factors.
- Ethical dilemmas surrounding access, fairness, and the potential for misuse.

Future Innovations
- Advances in wearable neurotechnology for continuous cognitive monitoring and enhancement.

Spoiler: Chapter 13: Ethical Horizons

Spoiler: Lesson 1: Addressing Inequity in Access

Introduction
As cognitive enhancement technologies and strategies advance, society must grapple with profound ethical, societal, and philosophical questions. The potential to augment human intelligence raises issues of fairness, accessibility, and the very nature of humanity. This chapter examines the ethical implications of cognitive enhancement, proposing frameworks for navigating these challenges while maximizing societal benefit.

Socioeconomic Disparities
- Advanced cognitive technologies risk creating a cognitive elite, further exacerbating social inequality.
- Barriers to access include high costs, limited availability, and geographic disparities.

Strategies for Equitable Distribution
- Subsidized public programs to democratize access to cognitive tools and training.
- International collaboration to ensure low income regions benefit from global advancements.

Case Studies
- Analysis of education technology programs that reduced learning disparities in underserved communities.
- Lessons from global vaccination campaigns in addressing accessibility challenges.

Spoiler: Lesson 2: Regulatory Frameworks for Innovation

Balancing Innovation and Safety
- The rapid pace of technological development often outstrips regulatory oversight, raising concerns about unintended consequences.
- Ethical considerations in human trials of neural implants and gene editing technologies.

Key Principles for Regulation
- Transparency: Ensuring clear communication of risks and benefits to all stakeholders.
- Accountability: Holding developers and practitioners responsible for misuse or harm.

Proposed Policies
- Establishing international standards for ethical research in cognitive enhancement.
- Guidelines for integrating Computer-driven systems into human decision-making processes.

Spoiler: Lesson 3: Redefining Humanity in an Era of Enhancement

Philosophical Implications
- What defines humanity when cognition becomes artificially enhanced?
- Exploring concepts of identity, autonomy, and authenticity in the context of augmentation.

Potential for Cognitive Stratification
- The division between enhanced and non-enhanced individuals could reshape societal structures.
- Ethical dilemmas surrounding informed consent for heritable genetic modifications.

Futurist Perspectives
- The cognitive singularity: Exploring scenarios where enhanced intelligence drives exponential societal transformation.
- Balancing individual freedom with collective responsibility in navigating the future of cognition.

Spoiler: Lesson 4: Ethical Dilemmas in Emerging Technologies

Brain-Computer Interfaces (BCIs)
- Risks of surveillance and data misuse in neural interfacing technologies.

Gene Editing and Cognitive Traits
- Ethical considerations in selecting or modifying traits for intelligence.
- Societal implications of normalizing genetic enhancement.

Neuropharmacology and Dependency
- Potential for misuse and addiction in cognitive enhancing drugs.
- Balancing short term performance gains with long term health risks.

Read every word of this unnecessarily long guide. Mirin the dedication

 

[Rigged]

R

Read every word of this unnecessarily long guide. Mirin the dedication

Appreciate it could u tell me what u thinks unnecessary curious for future reference

 

[Crusile]

Hunter literally contradicts u low comp jobs 0.23 medium 0.51 high 0.57 another case of u not reading ur own studies this would be like 10 fallacies by now

Yes this doesnt replicate. In the (2024) study I posted, low-complexity jobs had higher g-loading, indicating that IQ is more predictive of low-complexity gamified tasks than high complexity tasks. This follows the fact that IQ tests test your ability to solve culturally loaded, knowledge based, non-complex/gamified/simple tasks.

 

[Crusile]

Lets compare objective measures of "task" performance. IQ is a good predictor of video game performance and gun accuracy(simple/gamified), but not of a complex task that can be objectively measured, like sales. This also follows that assumption that IQ measures ability to preform non-complex tasks.

Does IQ Really Predict Job Performance? - PMC

IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test ...

pmc.ncbi.nlm.nih.gov

Perhaps it is hardly surprising, therefore, that supervisor ratings have rather low correlations with more objective criteria such as work samples or work output (Bommer, Johnson, Rich, Podsakoff, & Mackenzie 1995; Cook, 2009; Heneman, 1986). Schmidt, Hunter, and Outerbridge (1986) put it at virtually zero. In a study of salespersons, Vinchur, Schippmann, Switzer, and Roth (1998) found that “general cognitive ability” showed a correlation of .40 with supervisor ratings but only .04 with objective sales. Roth, Bobko, and McFarland (2005) found a mean observed correlation between work sample tests and measures of job performance (mostly supervisor ratings) of only 0.26, and a correlation between work sample tests and “general cognitive ability” of only 0.33. It is somewhat strange, therefore that Hunter (1986) reported that IQ/GMA predicted work sample ratings even better than it predicted supervisor ratings suggesting, perhaps, that they are measuring different things.

https://www.sciencedirect.com/science/article/abs/pii/S016028961500104X

The final model revealed a very high relationship between the high-order latent factors representing video game and intelligence performance (r = .93). General performance scores derived from video games and intelligence tests showed a correlation value of .963 (R2adjusted). Therefore, performance on some video games captures a latent factor common to the variance shared by cognitive performance assessed by standard ability tests.

 

[Crusile]

Iq tests measure GCA which is broader u fucktard, job specific knowledge tests predicts tasks already learned its useless for checking new problems

Job knowledge tests are better predictors than IQ because when you study for the job knowledge test that knowledge is gained and transferred. Knowledge tests measure your ability to learn while IQ tests measures your exposure to the western middle-class knowledge basis.

https://www.sciencedirect.com/science/article/abs/pii/S0160289608000603

While the SAT and ACT were highly g loaded, both tests generally predicted GPA after removing g. These results suggest that the SAT and ACT are strongly related to g, which is related to IQ and intelligence tests. They also suggest that the SAT and ACT predict GPA from non-g factors.

There is much more to "test taking ability" than g. IQ-like tests that are subjective specific are predictive after removing g, meaning IQ tests provide no additional predictive power. IQ = useless and have no utility

 

[AlphaLooksmaxxer666]

what iq tests are we talking about?>

 

[Rigged]

Yes this doesnt replicate. In the (2024) study I posted, low-complexity jobs had higher g-loading, indicating that IQ is more predictive of low-complexity gamified tasks than high complexity tasks. This follows the fact that IQ tests test your ability to solve culturally loaded, knowledge based, non-complex/gamified/simple tasks.

Lets compare objective measures of "task" performance. IQ is a good predictor of video game performance and gun accuracy(simple/gamified), but not of a complex task that can be objectively measured, like sales. This also follows that assumption that IQ measures ability to preform non-complex tasks.

Does IQ Really Predict Job Performance? - PMC

IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test ...

pmc.ncbi.nlm.nih.gov

https://www.sciencedirect.com/science/article/abs/pii/S016028961500104X

Job knowledge tests are better predictors than IQ because when you study for the job knowledge test that knowledge is gained and transferred. Knowledge tests measure your ability to learn while IQ tests measures your exposure to the western middle-class knowledge basis.

https://www.sciencedirect.com/science/article/abs/pii/S0160289608000603

There is much more to "test taking ability" than g. IQ-like tests that are subjective specific are predictive after removing g, meaning IQ tests provide no additional predictive power. IQ = useless and have no utility

Everything u just said is a regurgitation of what ive already replied to? R u lost in this “debate” maybe go read what u posted before since u clearly havent

1. Uve had like 20 fallacies
2. Regurgitating the arguements ive replied to aalready
3. Ignoring my points and assuming ur automatically right when i prove u wrong
4. Not reading a single one of the texts u sent or i sent blatantly
5. U sent studies that contradict urself
6. Arguing something that even ur studies agree with


Ur an embarrasment who doesnt know what hes talking about, i genuinely cant bother replying to a guy whose probably using AI to regurgitate the same info

 

[Crusile]

Everything u just said is a regurgitation of what ive already replied to? R u lost in this “debate” maybe go read what u posted before since u clearly havent

1. Uve had like 20 fallacies
2. Regurgitating the arguements ive replied to aalready
3. Ignoring my points and assuming ur automatically right when i prove u wrong
4. Not reading a single one of the texts u sent or i sent blatantly


Ur an embarrasment who doesnt know what hes talking about, i genuinely cant bother replying to a guy whose probably using AI to regurgitate the same info

Im repeating because you wont directly respond to the argument. all you do is post outdated p-hacked studies WITHOUT quotes so idk what to respond to. I responded to your p-hacked studies with newer studies that show that their findings dont replicate