IQ is nearly everything. Imagine a group with respectively different average IQs: 60, 80, 100, 120, 140, 160. Now imagine being able to have a discussion with the members of the groups. It goes without saying you would be able to assign respective numbers to every group.
There are extremely significant correlations between median average IQ and given professions (Schmidt Hunter 2004). The more prestigious and cognitively demanding the higher the median average arises. And there are also minimum requirements for each profession. Yes, we have elite lawyers with IQ 90, but there are just a few of them. The median is – predictably- very high.
This also applies to your performance in the job environment, your income, morbidity and mortality.
They also say every 5 IQ points is crucial in fields like programming, mathematics, physics, engineering, science and so on.
This article is an expansion of the old one. But this article tries to bring a vision of IQ was absolutely everything and an exact science.
A huge discovery, but it isn’t everything
The g factor, or general intelligence factor, was discovered in the early 20th century by British psychologist Charles Spearman. Spearman observed that individuals who performed well on one type of cognitive task tended to perform well on others. This suggests a common underlying ability. Through a method called factor analysis, he analyzed the correlations among various cognitive test scores. And found that they all shared a common variance, which he attributed to a single general intelligence factor, or g. Spearman proposed that this g factor represented a general cognitive ability that influences performance across a wide range of mental tasks.
Thus, Spearman’s discovery of the g factor had a profound impact on the field of psychology. This shaped our understanding of intelligence and cognitive abilities. His work laid the foundation for subsequent intelligence research and the development of IQ tests.
Intelligence psychometrics as exact as physics
“Every single mental process strategy and mental ability no matter what is equal to a measured IQ,” one could say if intelligence was something exact as physics.
Of course, we have an evolutionary-equiped mentality to persuade others to our opinions which is nothing but something self-serving. We have cognitive biases, fallacies, and formal logical errors, let’s make this vision without it. Just imagine an unimaginable – people are devoid of these.
“G factor” physics that knows the position of every neuron in your brain
This is another fine example that humanities cannot compete with exact sciences. If psychometrics were a truly exact science, it would have to know enormous complex interactions in the brain, at least of all that are connected with intelligence.
So it would have perfect knowledge (at least if it were as developed as modern physics is) of every neuron’s combinations which makes the the outcome for the final number.
I just want to make sure that the normal distribution (Gaussian curve) would still exist. And every single measured number of particular IQ would equal every final intellectual accomplishment.
Nowadays miserable (yet requiring an enormous IQ number of those scientists who made it) statistics tools would become completely obsolete.
No factor analysis, test construction and validation, no measuring of attention, long-term memory, perceptual speed, reasoning, and verbal ability.
All those indexes which I want to reiterate would be on the same scoring level and would be perfectly mathematicized.
If we want to simplify it, let’s do it mathematically
There would be enormously complicated equations and their geometrical equivalents.
Another example of how “little” psychometrics knows is by using neuroimaging techniques, such as MRI and fMRI, which have identified certain brain regions associated with general intelligence. Key areas include the prefrontal cortex, which is involved in executive functions and complex reasoning, and the parietal cortex, which is important for spatial and mathematical abilities. Higher connectivity and efficient neural networks in these areas often correlate with higher g.
All possible interactions in the brain
The human brain has approximately 86 billion neurons and between 100 trillion and 1000 trillion synapses. The number of possible combinations of these synapses is incredibly vast. If we consider the lower estimate of 100 trillion synapses, the number of potential combinations can be represented as two raised to the power of the number of synapses, which is two raised to 100 trillion. This number is so large it is practically beyond comprehension. It far exceeds the number of atoms in the observable universe, which is estimated to be around 10 to the power of 80.
How could be physically possible for different people to have the same constellation, and same intelligence?
If every single manifestation of intelligence would be solely ascribed to a particular number, the constellation in the brain must be the same. Well, it cannot be.
So while we would be able to grasp what intelligence is, people likely couldn’t have the same neurons interlinks, so IQ really isn’t everything.
Of course, goodbye G-loads
Since it would be an exact science, no “g loads” would be present. G-load, or g-loading, refers to the degree to which a test or task measures general intelligence, the g factor. We use this concept in psychometrics to indicate the extent to which performance on a particular cognitive test correlates with performance on a variety of other cognitive tasks – all of these tap into the underlying general intelligence.
A test with a high g-load is one that heavily relies on general cognitive ability rather than specific skills or knowledge. For example, tasks that involve abstract reasoning, problem-solving, and logical thinking tend to have high g-loads because they require the use of broad cognitive capabilities. In contrast, tasks that measure very specific skills or knowledge (e.g., a test on a particular historical event) may have lower g-loads because they are more reliant on specialized information rather than overall cognitive ability.
But why does it exist? The smart minds developing tests could have tailor-fit the tests so they would measure the sheer g factor (as it is in tests for super-intelligent people)!
Clinical psychologists use them to assess their patients (because the pathologies have basically unique IQ profiles.
Time to end the shallow theories and statistical methods
Make no mistake! I am too dumb to make any contributions but I just want to highlight that the theories – for the scientists really time-consuming – would have little relevance. In psychometrics just like physics, there would be some simplifaction, but their use would be limited:
Item Response Theory (IRT) models the relationship between an individual’s latent trait (intelligence) and their probability of correctly answering each test item.
IRT evaluates each item based on its difficulty, discrimination (how well it differentiates between individuals of different ability levels), and guessing parameters. This statistical model ensures that the test is sensitive to a wide range of abilities and provides more precise measurements at various levels of intelligence.
Goodbye, factor analysis!
Exploratory factor analysis (EFA): This method identifies the underlying relationships between measured variables without imposing a preconceived structure. It is often used to discover the potential factors that explain the observed correlations among different cognitive tests.
Confirmatory factor analysis (CFA): This method tests the hypothesis that the relationships among observed variables are explained by a specific factor structure. CFA confirms the existence of the g factor as a single underlying factor that influences various cognitive abilities.
Principal component analysis (PCA) is a technique used to reduce the dimensionality of data while retaining as much variability as possible. In the context of measuring the g factor, PCA helps to identify the principal components (or factors) that account for the most variance in cognitive test scores. The first principal component often represents the g factor.
Bifactor Model – each cognitive test score is influenced by both a general factor (g) and one or more specific factors. This model allows researchers to separate the variance attributable to the g factor from the variance attributable to specific abilities, providing a clear measure of general intelligence.
Structural equation modeling (SEM) combines factor analysis and path analysis, allowing for the modeling of complex relationships between observed and latent variables. In the context of measuring the g factor, we can use SEM to specify and test models that include the g factor and its relationships with various cognitive abilities.
Reliability is quantified using statistics like Cronbach’s alpha for internal consistency and correlation coefficients for test-retest reliability. High reliability indicates that the test consistently measures intelligence across different administrations and contexts.
There is talent and creativity, but IQ relevance should be a way above them
Of course, psychology clearly demonstrates that there are talents and creativity. But guess what? They are deeply interlinked with IQ.
However, if IQ was everything and every single mental ability was connected to it, there would be little space for talents and creativity
Intelligent in a broader or generalizable way? No, just “intelligent”
Folks that are intelligent only in IQ (not in a broader sense or generalizable way) may be highly performing pupils, high school or college and university students. Their mental processes are quick and patulous and they make great engineers, medical doctors, or – if their IQ is so high – scientists.
But they lack something that would make them intelligent not only in terms of IQ. For example, poor life choices (divorcing from someone good, marrying someone bad, having a child when burdened with pathogens, idebting despite obvious inability to pay the debt), inability to understand the world and make deductions, poor understanding the politics, easily being manipulated by fellow people or media, and remembering something important and being able to use it later on.
No, a particular IQ would be completely IQ for what we call “intelligence in a broader sense” or “intelligence in a generalizable way”.
These abilities should be based solely on IQ
Emotional intelligence: This encompasses the ability to understand and manage your own emotions, as well as recognize and influence the emotions of others. It involves empathy, self-awareness, and social skills that are crucial for effective interpersonal interactions and leadership.
Critical thinking: This skill involves the objective analysis and evaluation of information to form a judgment. It requires questioning assumptions, evaluating evidence, and considering alternative perspectives to make reasoned decisions.
Creativity: The capacity to generate new and original ideas, approaches, or solutions. Creativity is essential for innovation and problem-solving across various domains.
Decision-making: The process of making choices by identifying a decision, gathering information, and assessing alternative resolutions. Effective decision-making requires evaluating the potential impacts and benefits of different options.
Strategic thinking: This involves long-term planning and the ability to see the big picture. Strategic thinkers anticipate future trends and challenges to make informed decisions and set achievable goals.
Negotiation skills: The ability to engage in discussions to reach mutually beneficial agreements. This involves communication, persuasion, and understanding the interests of all parties involved.
Set #2
Leadership skills: The capability to guide, motivate, and inspire others toward achieving goals. Strong leadership involves vision, empathy, and the ability to foster collaboration and commitment.
Adaptability: The ability to adjust one’s approach or behavior in response to changing circumstances. Adaptability involves being open to new experiences and flexible in dealing with challenges.
Social intelligence: The skill to navigate social complexities and build positive relationships. It includes understanding social cues, managing interpersonal dynamics, and fostering effective communication.
Analytical skills: The capacity to assess complex information, identify patterns, and make data-driven decisions. Analytical skills are crucial for problem-solving and strategic planning.
Self-regulation: The ability to control one’s emotions, impulses, and behaviors. Self-regulation is important for maintaining focus, managing stress, and making thoughtful decisions.
Cognitive flexibility: This refers to the ability to switch between thinking about different concepts or to think about multiple concepts simultaneously. It is essential for adapting to new information and changing circumstances.
Judgment and decision-making: The ability to make considered decisions based on evaluating evidence and options. Good judgment involves balancing risks and benefits to choose actions likely to lead to positive outcomes.
Set #3
Metacognition: Awareness and understanding of one’s own thought processes. Metacognitive skills allow individuals to plan, monitor, and assess their understanding and performance, enhancing learning and problem-solving.
Resilience: The ability to recover quickly from difficulties and setbacks. Resilience helps individuals maintain performance under pressure and effectively bounce back from challenges.
Memory Skills: The capability to retain and recall information. Strong memory skills are vital for learning, problem-solving, and executing tasks accurately.
Intuition: The ability to understand something instinctively without conscious reasoning. Intuition can guide decision-making, especially in complex or uncertain situations.
Time management: The ability to plan and control how much time to spend on specific activities. Effective time management enhances productivity and ensures tasks are completed within deadlines.
Attention control: The ability to maintain focus on relevant stimuli while managing distractions. Good attention control is critical for efficient task completion and decision-making.
Ethical reasoning: The capacity to reflect on moral issues and determine the right course of action. Ethical reasoning involves evaluating the implications of decisions and actions based on moral principles.
Executive functioning: A set of cognitive processes including working memory, flexible thinking, and self-control. These skills are essential for managing oneself and achieving goals.
Numeracy skills: The ability to understand and work with numbers. Numeracy is crucial for tasks involving finance, budgeting, and statistical analysis.
Language skills: The ability to comprehend and produce language. Strong language skills enhance communication, comprehension, and persuasive abilities.
Visualization skills: The capability to imagine or visualize information, objects, or scenarios. Visualization is important in fields requiring spatial understanding and creativity.
Set #4
Perceptual speed: The ability to quickly and accurately process visual information. This skill is important for tasks requiring rapid decision-making and attention to detail.
Motivational skills: The ability to generate and sustain the drive to achieve goals. Motivation influences effort and persistence in tasks.
Self-efficacy: The belief in one’s ability to organize and execute actions required to manage situations. High self-efficacy can lead to increased confidence and perseverance.
Empathy: The capacity to understand and share the feelings of others. Empathy is essential for building strong relationships and effective leadership.
Impulse Control: The ability to resist or delay impulses and temptations. Impulse control is important for making deliberate and thoughtful decisions.
Pattern recognition: The skill to identify patterns and regularities in data. This is crucial for data analysis, strategic planning, and problem-solving.
Risk assessment: The ability to evaluate potential risks and benefits of different actions. This involves understanding probabilities and impacts to make informed decisions under uncertainty.
Moral reasoning: The ability to reason about ethical issues and dilemmas. It involves applying ethical principles to align decisions with one’s moral beliefs.
Systems thinking: The ability to understand and analyze complex systems and their interactions. Systems thinking is vital for problem-solving in fields like engineering and organizational management.
Conflict resolution: The ability to manage and resolve conflicts effectively. This involves communication, empathy, and problem-solving to find acceptable solutions.
Conceptual thinking: The ability to understand and think abstractly about complex ideas and theories. Conceptual thinkers see the bigger picture and connect seemingly unrelated concepts.
Self-reflection: The capacity to introspect and evaluate one’s own thoughts, feelings, and behaviors. Self-reflection is key for personal growth and self-improvement.
Insight: The ability to gain a deep understanding of people, situations, or concepts. Insight often involves recognizing underlying truths not immediately apparent.
Set #5
Goal setting: The ability to set realistic and achievable goals. Effective goal setting includes planning, motivation, and time management to reach desired outcomes.
Information processing: The ability to interpret and process information quickly and accurately. This skill is essential for tasks requiring rapid thinking and decision-making.
Numerical reasoning: The ability to apply numerical and mathematical concepts to solve problems. This skill is important in finance, engineering, and data analysis.
Perceptual reasoning: The capacity to interpret and make sense of visual information. This skill is crucial for tasks involving spatial awareness and visual-motor integration.
Deductive reasoning: The ability to draw specific conclusions from general information. Deductive reasoning is important for logical analysis and problem-solving.
Inductive reasoning: The ability to draw general conclusions from specific information. Inductive reasoning is useful for forming hypotheses and making predictions based on data.
Political opinions: Political opinions are shaped by an individual’s ability to analyze information and understand complex issues. Intelligence helps in forming well-reasoned views by evaluating evidence and understanding political dynamics, leading to informed decisions based on facts rather than biases.
Business choices: In business, intelligence is crucial for analyzing market trends and making strategic decisions. Political skills, such as negotiation and persuasion, aid in navigating corporate dynamics and influencing others. Combining these skills leads to effective business strategies and successful outcomes.
Extremely high IQ? Marilyn vos Savant, Christopher Langan
Marilyn vos Savant is an American author and columnist who gained fame for her record-breaking IQ score. Born on August 11, 1946, vos Savant was recognized by the Guinness Book of World Records for having the highest recorded IQ, estimated at 228 (but this is disputable as there is not enough people on the planet to recieve such a percentile). She capitalized on this recognition by writing the “Ask Marilyn” column in Parade magazine, where she answers various questions, puzzles, and problems posed by readers. Her column often tackles logical and mathematical problems, and she has written several books on topics ranging from intelligence to logic and problem-solving.
Vos Savant is particularly known for her involvement in the “Monty Hall problem,” a probability puzzle that generated widespread public interest and debate. Her solution to the problem, which involves switching choices to increase the probability of winning, was initially met with skepticism, even from mathematicians, but has since been mathematically verified. Beyond her column, vos Savant has worked on promoting the importance of logical thinking and education, contributing to discussions on intelligence and cognitive skills.
Christopher Langan
The mismeasure of her IQ
“Little Miss Savant was given an old version of the StanfordBinet (Terman & Merrill, 1937), which did, indeed, use the antiquated formula of MA/CA × 100. But in the test manual’s norms, the Binet does not permit IQs to rise above 170 at any age, child or adult. And the authors of the old Binet stated: “Beyond fifteen the mental ages are entirely artificial and are to be thought of as simply numerical scores” (Terman & Merrill, 1937, p. 31).
“In short, Marilyn vos Savant has always been unusually bright, amazingly gifted, and an extremely funny and entertaining columnist and author. Her “Ask Marilyn” column is often witty and brilliant. However, the psychologist who came up with an IQ of 228 committed an extrapolation of a misconception, thereby
violating most every rule imaginable concerning the meaning of IQs. Does an IQ of 228 make any sense? For an expert opinion, “Don’t Ask Marilyn.” (Kaufman, Alan S. (2009). IQ Testing 101.)
The smartest bouncer
Christopher Langan is an American autodidact known for his exceptionally high IQ, which is reported to be between 195 and 210 (see abovementioned rebuttal). Born on March 25, 1952, Langan has gained attention as one of the smartest individuals in America, despite not having a formal education beyond a few years of college. He worked in various labor-intensive jobs, including as a bouncer, while developing his theories on the nature of reality and the universe.
Langan is best known for his “Cognitive-Theoretic Model of the Universe” (CTMU), a comprehensive philosophical theory that attempts to explain the relationship between mind and reality. The CTMU proposes that reality is a self-simulating, self-configuring system, integrating aspects of theology, metaphysics, and mathematics. Although his work is largely self-published and has not gained mainstream acceptance in the scientific community, Langan has a dedicated following and continues to promote his theories through various platforms.
Stratospheric IQs and no results
Consequently, they should be top scientists, business leaders, the richest of the richest, smartest politicians, inventors, and so on. They (and not only them) should be on the top of the top.
But what the reality is? As I am infinite deviations below their IQs, I could not have answered the questions she did and barely could be successful in IQ tests just like they are.
But please read my blog (or someone’s else blog) and honestly answer this maybe impolite question. Could have they been able to do this? I am far away from being a genius, but I seriously doubt this.
A study of geniuses
One significant study on the socioeconomic outcomes of individuals with extremely high IQs is the Terman Study of the Gifted, initiated by psychologist Lewis Terman in the 1920s
He chose 1,500 children in California between the ages of eight and 12 who had an average IQ of 150. Of these, 80 had scored over 170. (Terman LM. Mental and Physical Traits of a Thousand Gifted Children. Genetic Studies of Genius, Volume 1. Stanford University Press.; Terman LM, Oden MH. Genetic Studies of Genius: The Gifted Group at Mid-Life; Thirty-Five Years’ Follow-Up of the Superior Child, Vol. 5. Stanford University Press.) (source)
The subjects’ average income in 1955 was $33,000, compared to a national average of $5,000.
Two-thirds had earned college degrees.
A large number had gone on to attain post-graduate and professional degrees.
Many of these had become doctors, lawyers, business executives, and scientists.
More than 50 became faculty members at colleges and universities.
This proves IQ means a lot, however, if IQ was everything, the results must have been really different.
We may know what is intelligence but is something vague
We have definitely solid knowledge of what intelligence is. People with IQs such as 160-180 may not be the top scientists, but the top scientists have such IQs.
It is a huge predictor, yet people highly differ in abilities, even though they are encircled around the “g factor”.
Bill Gates was asked: “What Microsoft competitor worries you most?” “Goldman Sachs and Morgan Stanley,” he replied. Because in software development, you need the people with the highest IQs.
Psychometrists are just like politicians – they leave criticism to their critics
They will tell you that IQ isn’t everything because they are like politicians, they defend their positions so vigorously that their subject of research is difficult to attack.
But here are some excemptions:
“The individual Wechsler subtests, or the subtests that compose the KAIT or WJ III, do not reflect the essential ingredients of intelligence whose mastery implies some type of ultimate life achievement. They, like tasks developed by Binet and other test constructors, are more or less arbitrary samples of behavior. Teaching people how to solve similarities, assemble blocks to match abstract designs, or repeat digits backward will not make them smarter in any broad or generalizable way.”
“What we are able to infer from the person’s success on the tasks and style of responding to them is important; the specific, unique aspect of intellect that each subtest measures is of minimal consequence. Limitations in the selection of tasks necessarily mean that one should be cautious in generalizing the results to circumstances that are from the one-on-one assessment of a finite number of skills and processing strategies. Intelligence tests should, therefore, be routinely supplemented by other formal and informal measures of cognitive, clinical, and neuropsychological functioning to facilitate the assessment of mental functioning as part of psychodiagnosis. The global IQ on any test, no matter how comprehensive, does not equal a person’s total capacity for intellectual accomplishment.” (Kaufman, Alan S.; Lichtenberger, Elizabeth (2006). Assessing Adolescent and Adult Intelligence (3rd ed.). Hoboken (NJ): Wiley)
A manifest criticizing their own work
Another aberration is 1995’s report “Intelligence: Knowns and Unknowns” which was published and signed by a lot of psychometrics heavyweights to provide a comprehensive and scientifically rigorous overview of the current understanding of intelligence. One primary reason for its publication was to clarify the scientific consensus on intelligence, dispelling myths and misconceptions that had proliferated in public discourse. By summarizing the state of research on intelligence, the report aimed to present a clear and authoritative account of what is known and unknown about the nature, measurement, and implications of intelligence.
Overall, the APA’s report highlights that while intelligence is an important factor in predicting life outcomes, it is not the sole determinant. A comprehensive understanding of human potential and achievement requires considering a wide range of genetic, environmental, and personal factors.
Although IQ scores are predictive of academic and occupational success, they do not account for all aspects of an individual’s abilities or potential. Non-cognitive factors such as motivation, emotional intelligence, and personality traits (like conscientiousness and perseverance) also play crucial roles in achieving success.
Conclusion
While the g factor is arguably one of the most statistically significant concepts in humanities, it is far away from being the exact science like mathematics, chemistry, or physics.
Even if we know every neuron position of a given individual, the concept would cease to make sense as the science would be extremely precise.
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