Recent research published in intelligence and cognitive ability It suggests that certain mental skills, such as technical knowledge, mathematics, and language skills, play an important role in predicting a person’s future income, educational attainment, and career path. This study provides evidence that these specific cognitive abilities are at least one-third more important than general intelligence in shaping a person’s social and economic position. This means education and career guidance programs can benefit from going beyond their overall intelligence scores to help people find paths that suit their unique strengths.
Tobias Edwards, a postdoctoral fellow in behavioral genetics and individual differences at the University of Minnesota, explained the motivation behind the study. “Intelligence is multidimensional,” Edwards says. “There’s your overall performance on cognitive ability tests, known as general intelligence, and then there’s your relative strengths and weaknesses, known as specific abilities.”
To explain this concept, Edwards pointed out that mental profiles can vary widely from person to person. “For example, someone who has generally average scores but performs well in language skills could be said to have strong language-specific abilities but average levels of general intelligence,” he said. General intelligence describes an individual’s overall ability to solve problems, think logically, and learn.
Psychologists often use standardized measures known as intelligence quotients (IQ scores) to estimate this potential ability. IQ scores are derived from cognitive tests and serve as a practical measure of a person’s general intelligence. Higher IQ scores consistently predict higher socio-economic status. Socioeconomic status refers to an individual’s class position, usually measured by a combination of education level, income, and job prestige.
Standard cognitive tests also measure specific abilities, such as speed of processing information, vocabulary, and mechanical knowledge. Early intelligence research found that performance on all cognitive tests tended to be positively correlated. People who do well on math tests also tend to do well on vocabulary tests. This phenomenon implies the existence of a general factor of intelligence that influences performance on all mental tasks. However, test scores also capture domain-specific abilities that function independently of general intelligence.
The authors of the new study argue that past studies examining specific abilities often used flawed mathematical methods. These previous studies often relied on calculating the difference between two test scores, such as subtracting a language score from a math score. This difference is known as tilt. The researchers argue that the tilt approach makes it impossible to know which specific abilities actually drive a person’s life outcomes.
The researchers note that the tilt method also does not adequately separate the influence of overall general intelligence from the specific skills being measured. Because of these methodological problems, many experts believed that specific abilities had little additional predictive power beyond general intelligence. “There is a consensus among intelligence researchers that general intelligence is far more important than specific abilities in predicting life outcomes,” Edwards said.
“I wanted to test that perspective, at least in terms of socio-economic outcomes such as income, occupation and education,” Edwards said. “We found that specific abilities, taken together, have about one-third to one-half as much predictive power as general intelligence when predicting these outcomes.” The authors aimed to use more sophisticated statistical models to precisely quantify the importance of specific abilities and understand how cognitive abilities guide career choices.
Researchers analyzed data from two large, nationally representative samples of the United States. They used the 1979 and 1997 National Longitudinal Surveys of Youth. The 1979 group included 11,914 participants who were 14 to 22 years old at the time of initiation, and the 1997 group included 7,008 participants who were 12 to 16 years old. Both groups completed the Military Vocational Aptitude Test, a multiple-choice test used by the military to assess mental skills and guide careers. Placement.
This battery includes 10 subtests that measure areas such as arithmetic reasoning, paragraph comprehension, general science, and knowledge of electronics and auto repair. The researchers adjusted scores for all tests to account for differences in gender, self-identified ethnicity, and age at which participants were tested. The scientists then used a statistical method called factor analysis. This process allowed them to separate overall general intelligence from three specific abilities, which they categorized as elements of skill, speed, and a combination of mathematics and language.
Technical competency includes practical vocational skills and is measured by testing automotive, shop, and electronics knowledge. Speed ability measured how quickly individuals completed simple mental tasks, such as converting numbers to letters. The mathematics and language components captured relative performance between mathematics-based and language-based tests. To track life outcomes, the authors looked at the highest level of education participants completed and their self-reported income over the years.
The researchers also calculated the prestige of the participants’ occupations. They assigned a socio-economic index score to each occupation. This is a weighted average of the typical income and education level of people working in that occupation. The data included information on family relationships, allowing the authors to identify full siblings. By comparing siblings raised in the same household, the researchers were able to control for the effects of common family education and parental background.
Scientists have found that certain abilities are highly correlated with predicting long-term socio-economic status. They calculated that specific abilities accounted for 30 percent to 57 percent of the importance of general intelligence in predicting education, income, and job prestige. These associations remained even when comparing siblings. This suggests that shared family environment does not fully explain the association between specific mental skills and life outcomes.
The influence of these cognitive abilities changed over the lifespan. Before age 25, general intelligence had a negligible effect on an individual’s income, but this effect increased significantly with age. Technology ability showed the opposite pattern, predicting positive earnings in the early 20s, followed by neutral or negative earnings later in life. Despite changing effects on income, technological proficiency consistently predicted lower educational attainment and lower overall occupational prestige across both generations.
The impact of technology ability on income also differed by gender. Higher technological capabilities tended to lead to higher earnings for men and lower earnings for women. The effects of speed and mathematical language ability were shown to be less consistent across the two different generations and to have different associations with income and education. Mathematical-linguistic factors predicted higher education and job prestige in the 1979 group, but only higher income in the 1997 group.
The study also showed evidence that people are grouped into specific occupations based on their cognitive strength. The average abilities of various occupations are broadly consistent with common stereotypes. Machinists, construction workers, and precision metal workers received high marks for their technical skills. Lawyers, judges, and religious workers were found to have low technical skills.
Professions such as engineering, medicine, and computer science were associated with high levels of mathematical and linguistic ability. Occupations that rely heavily on administrative tasks, such as secretaries and typists, showed high speed abilities. Farm workers and cleaners tended to score lower on speed ability.
Scientists calculated how concentrated occupations are in these cognitive abilities. The strongest clustering occurred in general intelligence. This means that work is highly categorized by overall intelligence. However, clustering around specific abilities was also significant. Sorting men into specific jobs based on their technological abilities was nearly 80% more powerful than categorizing them based on general intelligence.
The causal relationship between specific abilities and socio-economic outcomes remains unclear. “While our study was able to quantify predictions, it was not possible to determine causality,” Edwards said. “The extent to which specific abilities influence life outcomes is unknown.”
The associations observed in our data may be explained by other factors. “Another explanation for our findings may be that for young people our interests and favorite subjects can simultaneously influence not only our careers but also our particular abilities,” Edwards said. People who like cars are more likely to spend time learning about cars and score higher on their driving exams, mainly because they have a pre-existing interest.
Another potential limitation is that the test uses technical and mechanical questions with many characteristics. These topics are typically not found on standard intelligence assessments. This means that the high predictive power of technological ability may not emerge in studies that rely solely on traditional cognitive tests. The statistical structure of specific abilities also changed slightly between the 1979 and 1997 study groups.
These changes suggest that certain mental categories may change over time or between different forms of testing. Model misspecification may also be a factor, and the statistical categories researchers create may have slightly different underlying psychological characteristics mixed in. If the categories are not completely accurate, the measured effect may be slightly skewed.
Future research should investigate the causal relationships between personal interests, specific mental abilities, and subsequent social status. Understanding exactly how different cognitive profiles interact with economics can help educators adjust school curricula to develop the skills that are most useful to students.
The study, “More Than General Intelligence: Cognitive Abilities and Class Structure,” was authored by Tobias Edwards and Colin G. DeYoung.
