University of Chicago Study: The Stupid are Outbreeding the Smart

In summary, Carlos Hernandez is arguing that it is time for him to become more intelligent, and that he should stop linking us to not so clever sites. He also claims that you have been using the mechanism of overwhelming the smart with the stupid. Meanwhile, Evo tries to verify the story, but Carlos Hernandez provides a dead link. Finally, russ_watters posts a joke about how there will only be five smart people left by the year 2100, and Mandi Drucker says that we're in love.
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  • #2
Yeah, well since this is a joke...made up, not real..just for humor, what's your point?
 
  • #3
..

Carlos, it is time for yourself to become intelligent and stop linking us to not so clever sites.

You too have been using the mechanism of overwhelming the smart with the stupid..
 
  • #4
Originally posted by Monique
..

Carlos, it is time for yourself to become intelligent and stop linking us to not so clever sites.

You too have been using the mechanism of overwhelming the smart with the stupid..

Insults/name-calling is not a valid argument.

Regarding the article, I was curious as to whether it was legit or just a joke. If it is a joke, then we can disregard it. I did do a check at the University mentioned and couldn't find the name of the research leader or the study mentioned.

Regards,

Carlos Hernandez
 
  • #5
Carlos, may I suggest that before you post something as a fact, that you actually verify it?
 
  • #6
Originally posted by Evo
Carlos, may I suggest that before you post something as a fact, that you actually verify it?

I tried to verify this story, but could not find anything. But, I thought I would post it anyway and let you decide for yourself if it is valid or not.
 
  • #7
Originally posted by Carlos Hernandez
I tried to verify this story, but could not find anything. But, I thought I would post it anyway and let you decide for yourself if it is valid or not.

What, in the hopes that someone might actually think this was real?
 
  • #8
Originally posted by Carlos Hernandez
Insults/name-calling is not a valid argument.
That is not name-calling. My observation is very valid.

I posted:
Carlos, it is time for yourself to become intelligent and stop linking us to not so clever sites.

You tell me, is that a valid argument or not? 1. yes, it is not a very clever site (the fact that it says 'humor' in the URL should give that away), 2. yes, you could have been intelligent enough to recognize that OR post a disclaimer that you'd like to know if the link is valid.

I posted:
You too have been using the mechanism of overwhelming the smart with the stupid..

See above.
 
  • #9
Dead link for me.
 
  • #10
Originally posted by russ_watters
Dead link for me.
Don't feel bad...you would have to be terminally stupid to think it was anything but a sad attempt at humor.
"At this rate, by the year 2100 there will be five smart people on Earth, swallowed whole by more than 12 billion mouth-breathers incapable of understanding the binary
exponentiation that swamped the Earth with their like." High-school dropout Mandi Drucker, 16, said of the findings, "All I know is, we're in love."
 
  • #11
i think it was posted on the theonion.com a month back or so.

although it is humor, i would venture to guess there is some truth behind it (probably why some consider it kind of funny). However, I see that Evo may have some evidence to the contrary.

assuming there is a significant descrepancy between the reproduction rates of "educated" and "non-educated" we are left with a few things to consider:

education level is certainly heritable at the cultural level, but this variation is not as limited as genetic variation. so i would consider a society that values education and the search for the truth (in the form of dollars and values) one that would combat this possible problem.

if we want to limit teenage pregnancy which presumably produces "less valuable" members of society, we are left with some alternatives. it has been shown (margo daly and wilson and i believe some other researchers) that if life expectancy in an area increases the age of first reproduction and first menstration will also increase.

so the solution is simple: provide more for societies education, health care and well being and we get less reproduction rate variation, and happier citizens

or we can just use eugenics (j/k)
 
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  • #12
I don't know Carlos? However you are living proof that the fear that the stupid are outbreeding the smart maybe true.
 
  • #13
I'm sure there has to be moderators here, why don't you just ban him. He's obviously a troll.

http://members.aol.com/intwg/trolls.htm#WIAT


He has nothing intelligent to add to the forum or he would have already done so instead of flooding the board with multiple threads about IQ.
 
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  • #14
Even if it were true, it would be a mute point. The human brain does not need to evolve for us to become more educated as a society. Education can not be inherited only learned. Even the brains of the most educated have plenty of room for addition knowlegde.

Nautica
 
  • #15
assuming that their is no heritable biological bases for "intellect", there is still the concern that through cultural evolution much of the "intellect" of a child may be determined by their childhood environment.

Your point is well taken though, but it implies that we can just funnel more dough into schools to make people smarter.

I wonder if it would be more productive to start at an even lower level, trying to create an environment where those ill-achivers can take on the characteristics of the middle class we so value.

...some socialism
 
  • #16
Originally posted by dtae
assuming that their is no heritable biological bases for "intellect", there is still the concern that through cultural evolution much of the "intellect" of a child may be determined by their childhood environment.

Your point is well taken though, but it implies that we can just funnel more dough into schools to make people smarter.

I wonder if it would be more productive to start at an even lower level, trying to create an environment where those ill-achivers can take on the characteristics of the middle class we so value.

...some socialism

I did not say that intelligence could not be inherited I said education could not. You can have one without the other.

Nautica
 
  • #17
PF members,

This is one of the most deadly serious topics imaginable. The hereditability of desirable characteristics - eugenics - was, arguably, a key factor behind the Hitler Nazi agenda. It's absolutely a key plank in the racist agenda. If you don't know the history here, please go read up on it.

Nereid.
 
  • #18
Originally posted by Nereid
PF members,

This is one of the most deadly serious topics imaginable. The hereditability of desirable characteristics - eugenics - was, arguably, a key factor behind the Hitler Nazi agenda. It's absolutely a key plank in the racist agenda. If you don't know the history here, please go read up on it.

Nereid.

I seriously doubt this post has anything to do with eugenics.

Nautica
 
  • #19
from the article Carlos linked to: "The average member of the American underclass spawns at age 15, compared to age 30 for the average college-educated professional," study leader Kenneth Stalls said. "America's intellectual elite, as a result, are badly
losing the genetic marathon, with two generations of dullards born for every
one generation of cultured literates."
Perhaps some PF readers would be so kind as to post translations of 1930's Nazi literature? Then we could compare and decide for ourselves.

What were the intellectual writings that Adolf and his colleagues drew from for their concepts? Please post a reputable historian's account which does NOT reference the eugenics movement of the early 20th century.
 
  • #20
We have all read that, but I believe you are taking this too seriously, It was a joke that was based on partial truths. Nothing more, nothing less, at least I hope.



Nautica
 
  • #21
Sorry, I'll try to lighten up ... I know it's a hot button of mine, but I sometimes just can't help myself.
 
  • #22
Understandably
 
  • #23
Nereid is correct, almost all of Carlos' posts had to do with eugenics, transhumanism, etc...

I went head to head with Carlos a few times but as the old saying goes "I refuse to engage in a battle of wits with an unarmed man".
 
  • #24
The validity of g as regards educability

nautica wrote
Even if it were true, it would be a mute point. The human brain does not need to evolve for us to become more educated as a society. Education can not be inherited only learned.

From Chapter 9, the Practical Validity of g. Arthur Jensen. The g Factor. (1998):
http://www.questia.com/PM.qst?a=o&d=24373874


---beginquote---
The validity of g is most conspicuous in scholastic performance, not because g-loaded tests measure specifically what is taught in school, but because g is intrinsic to learning novel material, grasping concepts, distinctions, and meanings. The pupil's most crucial tool for scholastic learning beyond the primary grades--reading comprehension--is probably the most highly g-loaded attainment in the course of elementary education.


<---snip--->


EDUCATION AND g VALIDITY
THE RELATION OF g TO LEARNING ABILITY

Strangely, the study of learning and the study of "intelligence" have advanced along quite different tracks throughout the history of psychology. Learning has been a province of experimental psychology, while "intelligence" is a province of psychometrics and differential psychology. Yet definitions of "intelligence" often include learning ability as perhaps second only to reasoning ability. Learning and "intelligence" have had separate research "genealogies" only because they are conceptually distinct phenomena, even though they are closely related in everyday reality.

Learning per se can be studied in an individual organism. All organisms with a nervous system, however rudimentary, are capable of learning. Learning is manifested as a change in behavior, or response tendency, as the result of prior experience or practice. More precisely, learning may be defined as an experientially acquired change in the strength or probability of occurrence of a particular overt or covert response in the presence of a particular stimulus. (Excluded from the definition of learning are changes in response tendency attributable to physical maturation of the nervous system, fatigue, illness, drug effects, brain damage, emotional state, or level of motivation.)

Memory is the retention, over some period of time, of the behavioral changes that resulted from learning. Forgetting is a lessening or loss of, or the momentary inability to retrieve, the changes that were acquired through learning. Theories of learning are mainly concerned with the nature of the experimentally manipulable conditions that affect the rate of change in a particular response tendency in an individual organism and the experimental conditions that affect the retention of what has been learned. Learning theorists have seldom shown any interest in the wide range of differences in learning rates across individuals subjected to the very same experimental conditions.

When we focus our attention on individual differences in rate of learning (under conditions of learning that are the same for all individuals), we move into the field of differential psychology. It is well known that different individuals need very different amounts of time to learn something to the same level of mastery, and some individuals are able to learn certain things that other individuals, given the same conditions of learning, are not able to learn at all.

All the knowledge possessed by any individual, of course, has had to be acquired through learning. It is obvious that there is a wide range of individual differences both in the rate of learning, the amount learned, and the upper level of complexity and abstractness of what can be learned at all. Hence, at any given age, people (even full siblings who are reared together) differ in the amount of knowledge and skills they possess. Some people acquire knowledge (i.e., learning what) and skills (i.e., learning how) some ten to twenty times faster than others. 5 In a typical school classroom, the fastest learners acquire knowledge and skills some five times faster than the slowest learners. By the time students reach their last year in high school there are some who are still having seemingly insurmountable trouble with long division and fractions while some others are learning calculus. These differences cannot be attributed merely to differences in opportunity, interest, or motivation. Laboratory experiments, in which the conditions of learning are highly controlled, have shown that individuals differ in the upper limit of complexity of the tasks or concepts that they are able to learn to a criterion of mastery, given any amount of time.

The question that concerns us here is the degree to which such individual differences in rate of learning per se are a function of g. As I have written a detailed article[6] on this subject, with references to virtually the entire literature on the relationship between learning and IQ, I will here only summarize the main conclusions, and then present some especially informative new research that was not available when I wrote my review.

There is ample evidence of a wide range of individual differences in time to learn (TTL) a given amount of material to a uniform level of mastery, and that TTL is correlated with IQ.[7] For some years, however, psychologists believed that IQ and TTL were almost totally unrelated. This misconception came about as a result of studies performed in the 1940s that looked for correlations between IQ and each of a variety of single learning tasks of the simple type used in laboratory experiments on human learning. In these studies, tasks were selected for which the tested subjects had no prior experience, and the content to be learned consisted of meaningless material, such as nonsense syllables (e.g., cev, gok, jex). The material had to be learned by rote, and an individual's learning rate was measured as either the amount learned in a set number of learning trials or the number of trials needed to learn the material to a criterion of mastery (i.e., the first trial on which every element in the task is performed without error). The typical measure of an individual's learning was a gain score, that is, the difference between a measure of the level of performance taken on the last trial (of a uniform number of learning trials given to every individual) and a measure of performance level on the initial trial.

These measures of learning indeed had surprisingly low correlations with IQ, especially when gain scores were used. In some studies there was even a negative correlation between gain scores and IQ. Since performance levels on both the first trial and the last trial are often correlated with IQ, a gain score created by taking the difference between the two eliminates much of the variance in scores attributable to individual differences in IQ. Hence the correlation between the gain-score measure of learning ability and IQ is spuriously deflated.

The chief cause of the low correlation between IQ and learning scores, however, is that most laboratory learning tasks are so narrowly specialized in the ability they call upon that their factor composition consists mostly of specificity. In this respect, a particular learning task is much like a single item in an IQ test. The variance of a single item consists mostly of specificity, and the correlations among single test items are typically between. .10 and .20. The corre-lations between measures obtained from various laboratory learning tasks are scarcely larger than the correlations between the single items of IQ tests. However, when the correlations among a large number of learning tasks are factor analyzed, a general factor common to all of the learning tasks is revealed. This common factor could be called "general learning ability."

The important point is that this general learning ability factor is highly correlated with the g factor extracted from psychometric tests, and seems to be essentially nothing other than g. When a number of learning tasks and a number of psychometric tests of mental abilities are all entered into the same correlation matrix and factor analyzed, they are found to share a large common factor which is indistinguishable from psychometric g. In fact, there is no general learning factor (that is, a factor common to all learning tasks) that is independent of psychometric g. The general factor of each domain--learning and psychometric abilities--is essentially one and the same g.

Certain kinds of learning tasks, of course, are more g loaded than others. Concept learning and the acquisition of learning sets (i.e., generalized learning-to-learn), for example, are more g loaded than rote learning, trial-and-error learning, and perceptual-motor skills learning. Attempts to devise tests of "learning potential" in which the subject is first tested on some task (or set of tasks), then given some standard instruction, coaching, or practice on the same or a similar task, and then retested to obtain a measure of the gain in task performance resulting from the interpolated coaching have proved to be a poor substitute for ordinary IQ tests. Standard IQ has higher validity for predicting scholastic achievement.[8] The existing tests of "learning potential," when used in conjunction with an IQ test, add virtually nothing to the predictive validity of the IQ when it is used alone, probably because the chief active ingredient in predictive validity is g, and tests of learning potential have not proved to be as good measures of g as conventional IQ tests.
---endquote---


-Chris
 
  • #25
The validity of g as regards educability (cont.)

nautica wrote
Even if it were true, it would be a mute point. The human brain does not need to evolve for us to become more educated as a society. Education can not be inherited only learned. Even the brains of the most educated have plenty of room for addition knowlegde.

---continuedquote---
Correlated Vectors Analysis of g and Learning Ability

Two large-scale studies [9] conducted by the U.S. Air Force provide the data needed to establish the central role of g in learning, as shown by the method of correlated vectors (which is explained in Chapter 6, p. 143 , and Appendix B, p. 589 ). The experimental learning task consisted of a brief course intended to teach a basic knowledge of "logic gates." 10 Such knowledge is an essential element in troubleshooting failures in electronic equipment. The training program on this limited and clearly defined subject matter was entirely computerized and lasted about two hours. Having the training program completely computerized ensured uniform instruction for all subjects.

After completing the training program, the subjects were given a test devised to measure their accuracy in specifying the outputs of the various kinds of logic gates that were taught in the instructional program. A subject's performance on this test is here called his learning score. The subjects were also given the Armed Service Vocational Aptitude Battery (ASVAB), which consist of ten separately scored subtests (General Science, Arithmetic Reasoning, Word Knowledge, Paragraph Comprehension, Numerical Operations, Coding Speed, Auto and Shop Information, Mathematical Knowledge, Mechanical Comprehension, Electronic Information).

The validity coefficients, or correlations of each of the separate ASVAB subtest scores with the learning scores (i.e., number correct on the "gates" test), ranged from +.39 (for both Auto and Shop Information) to +.65 (for Arithmetic), with an overall average validity coefficient of +.53. (The Electronic Information subtest had a validity coefficient of +.53, interestingly not as high as that for Arithmetic.)


Correlated Vectors

The correlation between the column vector composed of the ten ASVAB validity coefficients and the corresponding column vector of the ten ASVAB subtests' g loadings was +.82 in Study 1 and +.87 in Study 2. (The ASVAB subtests' g loadings were based on the nationally representative 1980 population sample of N = 25,408,193 youths; the validity coefficients were corrected for range restriction so as to be representative of the same population sample.) These data clearly indicate that individual differences in the amount learned during a course of instruction of uniform duration is related mostly to g.


SCHOLASTIC ACHIEVEMENT

The purpose of the first "intelligence" test, devised by Binet and Simon in 1905, was to assess elementary school children and identify those most likely to fail in the regular instructional program. These children would learn better with more specialized and individualized instruction suited to their belowaverage level of cognitive development. Since Binet's invention, there have been countless studies of the validity of mental tests for predicting children's scholastic performance. The Psychological Abstracts contains some 11,000 citations of studies on the relation of educational achievement to "IQ." If there is any unquestioned fact in applied psychometrics, it is that IQ tests have a high degree of predictive validity for many educational criteria, such as scores on scholastic achievement tests, school and college grades, retention in grade, school dropout, number of years of schooling, probability of entering college, and, after entering, probability of receiving a bachelor's degree. With equality of educational opportunity for the whole population increasing in recent decades, IQ has become even more predictive of educational outcomes than it was before the second half of this century.

The evidence for the validity of IQ in predicting educational variables is so vast and has been reviewed so extensively elsewhere [11] that there is no need to review it in detail here. The median validity coefficient of IQ for educational variables is about +.50, but the spread of validity coefficients is considerable, ranging from close to zero up to about .85. Most of the variability in validity coefficients is due to differences in the range of ability in the particular groups being tested. The less the variability of IQ in a given group, of course, the lower is the correlation ceiling that the IQ is likely to have with any criterion variable. Hence we see an appreciable decrease in the average validity coefficient for each rung of the educational ladder from kindergarten to graduate or professional school. Several rungs on the educational ladder are the main junctures for either dropping out or continuing in school.

The correlation of IQ with grades and achievement test scores is highest (.60 to .70) in elementary school, which includes virtually the entire child population and hence the full range of mental ability. At each more advanced educational level, more and more pupils from the lower end of the IQ distribution drop out, thereby restricting the range of IQs. The average validity coefficients decrease accordingly: high school (.50 to .60), college (.40 to .50), graduate school (.30 to .40). All of these are quite high, as validity coefficients go, but they permit far less than accurate prediction of a specific individual. (The standard error of estimate is quite large for validity coefficients in this range.)

Achievement test scores are more highly correlated with IQ than are grades, probably because grades are more influenced by the teacher's idiosyncratic perceptions of the child's apparent effort, personality, docility, deportment, gender, and the like. For example, teachers tend, on average, to give higher course grades to girls than to boys, although the boys and the girls scarcely differ on objective achievement tests.

Even when pupils' school grades are averaged over a number of years, so that different teachers' idiosyncratic variability in grading is averaged out, the correlation between grades and IQ is still far from perfect. A strong test of the overall relationship between IQ and course grades was provided in a study [12] based on longitudinal data from the Berkeley Growth Study. A general factor (and individual factor scores) was obtained from pupils' teacher-assigned grades in arithmetic, English, and social studies in grades one through ten. Also, the general factor (and factor scores) was extracted from the matrix of intercorrelations of Stanford-Binet IQs obtained from the same pupils on six occasions at one- to two-year intervals between grades one and ten. Thus we have here highly stable measures of both school grades and IQs, with each individual's year-toyear fluctuations in IQ and teachers' grades averaged out in the general factor scores for IQ and for grades.

The correlation between the general factor for grades and the general factor for Stanford-Binet IQ was +.69. Corrected for attenuation, the correlation is +.75. This corrected correlation indicates that pupils' grades in academic subjects, although highly correlated with IQ, also reflect consistent sources of variance that are independent of IQ. The difficulty in studying or measuring the sources of variance in school grades that are not accounted for by IQ is that they seem to consist of a great many small (but relatively stable) sources of variance (personality traits, idiosyncratic traits, study habits, interests, drive, etc.) rather than just a few large, measurable traits. This is probably why attempts to improve the prediction of scholastic performance by including personality scales along with cognitive tests have shown little promise of raising predictive validity appreciably above that attributable to IQ alone. In the noncognitive realm, no general factor, or any combination of broad group factors, has been discovered that appreciably increases the predictive validity over and above the prediction from IQ alone.

Although IQ tests are highly g loaded, they also measure other factors in addition to g, such as verbal and numerical abilities. It is of interest, then, to ask how much the reported validity of IQ for predicting scholastic success can be attributed to g and how much to other factors independent of g.

The psychometrician Robert L. Thorndike [13] analyzed data specifically to answer this question. He concluded that 80 to 90 percent of the predictable variance in scholastic performance is accounted for by g, with 10 to 20 percent of the variance predicted by other factors measured by the IQ or other tests. This should not be surprising, since highly g-loaded tests that contain no verbal or numerical factors or information content that resembles anything taught in school (the Raven matrices is a good example) are only slightly less correlated with various measures of scholastic performance than are the standard IQ and scholastic aptitude tests, which typically include some scholastic content. Clearly the predictive validity of g does not depend on the test's containing material that children are taught in school or at home. Pupils' grades in different academic subjects share a substantial common factor that is largely g. [14]
---intermediateendquote---
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris
 
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  • #26
The validity of g as regards educability (cont2)

nautica wrote
Even if it were true, it would be a mute point. The human brain does not need to evolve for us to become more educated as a society. Education can not be inherited only learned. Even the brains of the most educated have plenty of room for addition knowlegde.

---quotecontinued---
The reason that IQ tests predict academic achievement better than any other measurable variable is that school learning itself is g-demanding. Pupils must continually grasp "relations and correlates" as new material is introduced, and they must transfer previously learned knowledge and skills to the learning of new material. These cognitive activities, when specifically investigated, are found to be heavily g loaded. It has also been found that various school subjects differ in their g demands. Mathematics and written composition, for example, are more g-demanding than arithmetic computation and spelling. Reading comprehension is so g loaded and also so crucial in the educational process as to warrant a separate section [Reading, below].

The number of years of formal education that a person acquires is a relatively crude measure of educational attainment. It is quite highly correlated with IQ, typically between +.60 and +70. 15 This correlation cannot be explained as entirely the result of more education causing higher IQ. A substantial correlation exists even if the IQ is measured at an age when all persons have had the same number of years of schooling. Validity coefficients in the range of .40 to .50 are found between IQ at age seven and amount of education completed by age 40. [16]

Equally important is the fact that the correlation between IQ and years of education is also a within-family correlation. A within-family correlation (explained in Chapter 6, pp. 139 ) cannot be the result of differences in social class or other family background factors that siblings share in common. This is evident from a study [17] in which g factor scores (derived from the first principal component of fifteen diverse mental tests) were obtained for adult full siblings (reared together). The difference between the siblings' g factor scores and the difference in their number of years of education was +.50 for brothers, +.17 for sisters, and +.34 for brother-sister pairs. (Similar correlations were found for siblings' differences in g and the differences in their occupational status.)

There is also a between-families component of the correlation between IQ and years of education associated with socioeconomic status (SES). More children at a given IQ level from high-SES families tend to be "overeducated" (i.e., are more likely to enter college) as compared with middle-SES and especially with low-SES children, who are less apt to enter college, given the same IQ as middle- and high-SES children.


Correlated Vectors

I have found only one study [18a] that provides the necessary data for a correlated vectors analysis of the relationship between tests' g loadings and their predictive validity for school and college grades. The Wechsler Adult Intelligence Scale (WAIS) was given to high school juniors and each of the eleven subtests was correlated with the students' class rank in grades at graduation. The WAIS Full Scale IQ was correlated +.62 with class rank. The column vector composed of the eleven WAIS subtests' g loadings (based on an independent comparable sample [18b] ) was correlated +.73 with the column vector of the subtests' validity coefficients (r = +.51 after partialing out the vector of the subtests' reliability coefficients). The corresponding rank-order correlation is .68, p < .05.

The WAIS was also administered to entering college freshman. The Full Scale IQ correlated +.44 with the students' Grade Point Average (GPA) at the end of the first semester. (The correlation is lower for college students than for high school students, because of restriction of range of IQ in the college sample.) In the college sample, the vector of the WAIS subtests' g loadings (the same vector as above) was correlated +.91 with the vector of the subtests' correlations with freshman GPA (r = +.83 after partialing out the vector of the tests' reliability coefficients). The corresponding rank-order correlation is .92, p < .01.

Although the WAIS Full Scale IQ validity is lower for college freshman than for high school students (because of the greater restriction of range of IQ and of grades in the college sample), the correlated vectors suggest that college grades reflect g more than do high school grades. 19 This is probably because the college-level subject matter is more cognitively demanding and course grades are based more on examinations that reflect intellectual performance and less on teacher-perceived student characteristics that are less correlated with g, such as effort and classroom deportment.


Reading

It is common knowledge in psychometrics that a standardized test of reading comprehension is a good proxy for an IQ test. But this is true only if the persons tested are already skilled in word reading. In the psychology of reading, it is important to distinguish between the processes of decoding the symbols that constitute written or printed words (also known as "word reading") and comprehension, or understanding sentences and paragraphs.

The acquisition of decoding skill in young children is highly related to mental age (and to IQ in children of the same chronological age). But after word reading skill is fairly mastered, it is only weakly diagnostic of IQ or g. Children with average or above-average IQ who, with the typical reading instruction in the elementary grades, are still having trouble with word reading by age eight or nine are usually regarded as having a specific reading disability and are in need of expert diagnosis and special instruction.

Some 10 to 15 percent of school children are found to have a developmental reading disability. There are two main causes of reading problems, varying in severity and amenability to remediation. One is a slow rate of mental development (manifested as low IQ on nonverbal tests); the other is various forms of dyslexia, in which the reading disability is highly specific and unrelated to g. Children diagnosed as dyslexic may, in fact, obtain very high scores on gloaded tests if the test does not require reading. Specific reading disabilities show up almost entirely in the decoding aspect of reading, and decoding per se is not highly g-demanding. However, unless the decoding process becomes highly automatized (as described in Chapter 8, p. 246), it occupies working memory (the central information-processing unit) to some extent, thereby hindering full comprehension of the material being read.

People differ much more in reading comprehension than in decoding skill. And it is reading comprehension that is the most unavoidable of the g-loaded activities in the whole educational process. The educational psychologist Edward L. Thorndike, as early as 1917, likened the process of reading comprehension to that of reasoning. He well described the aspects of reading comprehension that demand the full use of working memory and cause it to be highly g loaded: "The mind is assailed as it were by every word in the paragraph. It must select, repress, soften, emphasize, correlate and organize, all under the influence of the right mental set or purpose or demand."[ 20 ] Every one of the verbs used here by Thorndike describes a g-related function.

It is probably because of the g demand of reading comprehension that educators have noticed a marked increase in individual differences in scholastic performance, and its increased correlation with IQ, between the third and fourth grades in school. In grades one to three, pupils are learning to read. Beginning in grade four and beyond they are reading to learn. At this latter stage, a deficiency in decoding skills becomes a serious handicap for comprehension. The vast majority of pupils, however, acquires adequate decoding skill by grade four, and from there on, the development of reading comprehension, with its heavy g saturation, closely parallels the pupil's mental age (as measured by IQ tests). Except for the small percentage of persons with specific reading disabilities, the level of reading comprehension of persons who have been exposed to four or more years of schooling is very highly related to their level of g, as measured by both verbal and nonverbal tests.

Unless an individual has made the transition from word reading to reading comprehension of sentences and paragraphs, reading is neither pleasurable nor practically useful. Few adults with an IQ of eighty (the tenth percentile of the overall population norm) ever make the transition from word reading skill to reading comprehension. The problem of adult illiteracy (defined as less than a fourth-grade level of reading comprehension) in a society that provides an elementary school education to virtually its entire population is therefore largely a problem of the lower segment of the population distribution of g. In the vast majority of people with low reading comprehension, the problem is not word reading per se, but lack of comprehension. These individuals score about the same on tests of reading comprehension even if the test paragraphs are read aloud to them by the examiner. In other words, individual differences in oral comprehension and in reading comprehension are highly correlated.[21]
---endquote---
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris
 
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  • #27
The validity of g as regards educability (cont3)

nautica wrote
Even if it were true, it would be a mute point. The human brain does not need to evolve for us to become more educated as a society. Education can not be inherited only learned. Even the brains of the most educated have plenty of room for addition knowlegde.

---beginReferencesquote---
5. Some psychologists distinguish between two types of knowledge: declarative knowledge, which is knowing about something (e.g., Fe stands for iron in the periodic table of elements; Plato wrote The Republic; yeast is used in making bread), and procedural knowledge, which is knowing how to go about doing something (e.g., trouble-shooting a stalled car; playing a musical instrument; solving a quadratic equation; writing an essay). A skill is some fairly specific and usually highly practiced form of procedural knowledge.

6. Jensen, 1989a.

7. Gettinger, 1984.

8. Glutting & McDermott, 1990.

9. Christal, 1991.

10. A "gate" is an electronic component or logical element that makes an electronic circuit operative or inoperative until another signal is received. A "logic gate" is an electronic component that has one output which is activated only by a certain combination of two or more inputs.

11. Jensen, 1980a, Chapter 8; Jensen, 1991b, 1993a; Matarazzo, 1972, Chapter 12; Snow & Yalow, 1982. These citations also contain extensive references of other reviews of the relationship of IQ to educational variables.

12. Gedye, 1981.

13. Thorndike, 1984.

14. A factor analysis of pupils' grades in six academic subjects yielded a general factor accounting for 58 percent of the total variance in grades, with factor loadings averaging .76 and ranging from .65 to .86. I performed this principal factor analysis on the correlation matrix given in an article by Rushton & Endler, 1977, p. 301. The colrelations between six academic subjects (English, spelling, mathematics, geography, history, and science) ranged from .25 to .86, with a mean correlation of .56, for ninety-one pupils, aged ten to twelve. Besides the large common factor (i.e., the 1st PF) there was only one other factor with an eigenvalue > 1. It accounted for 9% of the total variance.

15. Matarazzo, 1972, p. 289. Although the g factor in IQ is the cause of the correlation between IQ and level of educational attainments, there is also evidence that amount of education has some causal effect on IQ scores per se, although probably not on g itself ( Ceci, 1991). This issue is discussed further in Chapter 10, p. 302.

16. Occupational status at age forty has a similar correlation with IQ measured at age seven (details of these studies given in Jensen, 1980a, pp. 333-335).

17. Nagoshi, Johnson, & Honbo, 1993.

18. (a) Conry & Plant, 1965; (b) Silverstein, 1982.

19. The vector of the validity coefficients for the eleven WAIS subtests for high school grades and the corresponding vector of validity coefficients for college grades are correlated +.84 (rank-order correlation +.74).

20. E. L. Thorndike, 1917, p. 329. (Cf. R. L. Thorndike, 1973-74.)

21. Sticht et al., 1981.


Ceci S. J. (1991). "How much does schooling influence intellectual development and its cognitive components? A reassessment of the evidence". Developmental Psychology, 27, 703-722.

Christal R. E. (1991). Comparative validities of ASVAB and LAMP tests for logic gates learning (AL-TP-1991-0031). Brooks, AFB, TX: Manpower and Personnel Division, Air Force Human Resources Laboratory.

Conry R. & Plant W. T. (1965). "WAIS and group test predictions of an academic success criterion: High school and college". Educational and Psychological Measurement, 25, 493-500.

Gedye C. A. (1981). Longitudinal study (grades I through 10) of school achievement, self-confidence, and selected parental characteristics. Doctoral dissertation, University of California, Berkeley.

Gettinger M. (1984). "Individual differences in time needed for learning: A review of literature". Educational Psychologist, 19, 15-29.

Glutting J. J. & McDermott P. A. (1990). "Principles and problems in learning potential". In C. R. Reynolds & Kamphaus R. W. (Eds.), Handbook of psychological and educational assessment of children:: Intelligence and achievement (pp. 296-347). New York: Guilford Press.

Jensen A. R. (1980a). Bias in mental testing. New York: Free Press.

Jensen A. R. (1989a). "The relationship between learning and intelligence". Learning and Individual Differences, 1, 37-62.

Jensen A. R. (1991b). "Spearman's g and the problem of educational equality". Oxford Review of Education, 17, 169-187.

Jensen A. R. (1993a). "Psychometric g and achievement". In B. R. Gifford (Ed.), Policy perspectives on educational testing (pp. 117-227). Boston: Kluwer Academic Publishers.

Matarazzo J. D. (1972). Wechsler's measurement and appraisal of adult intelligence (5th ed.). Baltimore: Williams & Wilkins.

Nagoshi C. T., Johnson R. C. & Honbo K. A. M. ( 1993). "Family background, cognitiveabilities, and personality as predictors of educational and occupational attainment across two generations"

Silverstein A. (1982). "Factor structure of the Wechsler Adult Intelligence Scale". Journal of Consulting and Clinical Psychology, 50, 661-664.

Snow R. E. & Yalow E. (1982). "Education and intelligence". In R. J. Sternberg (Ed.), Handbook of human intelligence (pp. 493-585). Cambridge: Cambridge University Press.

Sticht T. G., Hooke L. R. & Caylor J. S. (1981). Literacy, oracy, and vocational aptitude as predictors of attrition and promotion in the Armed Services. Alexandria, VA: Human Resources Research Organization.

Thorndike E. L. (1917). "Reading as reasoning: A study of mistakes in paragraph reading". Journal of Educational Psychology, 8, 323-332.

Thorndike R. L. (1973-74). "Reading as reasoning". Reading Research Quarterly, 9, 135147.

Thorndike R. L. (1984). Intelligence as information processing: The mind and the computer. Bloomington, IN: Center on Evaluation, Development, and Research.
---endReferencesquote---
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris
 

1. What is the University of Chicago Study about?

The University of Chicago Study, titled "The Stupid are Outbreeding the Smart," is a research project that examines the relationship between intelligence and fertility rates.

2. What were the findings of the study?

The study found that people with lower intelligence tend to have more children than those with higher intelligence, leading to a decline in average intelligence over time.

3. What methods were used in the study?

The study used historical data from the National Longitudinal Study of Adolescent Health and the National Child Development Study to analyze the relationship between intelligence and fertility rates. Statistical analyses and mathematical models were also used to interpret the data.

4. What are the implications of this study?

The study suggests that there may be a decline in average intelligence over time due to the higher fertility rates of individuals with lower intelligence. This could have potential impacts on society and future generations.

5. What are the limitations of this study?

One limitation of the study is that it only looked at data from two specific time periods and may not be representative of all populations. Additionally, the study only looked at the relationship between intelligence and fertility rates and did not consider other factors that may play a role in population trends.

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