ヘンリー・H・ゴダード(英語版)は優生学者だった。1908年、彼は自身のバージョンである『The Binet and Simon Test of Intellectual Capacity』を発表し、この検査を親切に宣伝した。彼はすぐにこの尺度の使用を公立学校(1913年)、移民(エリス島、1914年)、法廷(1914年)に拡大した[48]。
知能の偏差値を「知能偏差値 (Intelligence Standard Score, ISS)」という。これは、知能を偏差値の形で表示したものであり、50を中心として上に行くほど知能が高いことをあらわしている。特徴としては、母集団の結果にばらつきが多い年齢層とばらつきが少ない年齢層の両方で、正確な表示ができることなどがあげられる。また、標準学力検査の結果も学力偏差値で表示される場合が多いため、IQと学力は比較しにくいが、知能偏差値と学力は比較しやすいという特徴もある。また、DIQはもともと偏差値・標準偏差の考え方を利用した表示法なので、知能偏差値はDIQと簡単に換算できる。伝統的に集団式検査に多い表示法である。
1969年にアーサー・ジェンセンは「いかにしてIQと成績を向上させられるか」と言う論文で、アメリカにおける人種間の成績の差はそれまで暗黙に仮定されていたように、環境と学習だけの差ではなく、遺伝的差異が関わっている可能性も考慮するべきだと述べて論争を巻き起こした。1994年には『ベル・カーブ』 (The Bell Curve) という845ページの本が、リチャード・ハーンシュタインとチャールズ・マレーによって執筆された。二人は人種間の遺伝的差異は主張しなかったが、やはり知能は環境と学習だけで決定するのではなく個人間に遺伝的差異があり、社会的地位の高い人々と低い人々の間で知能の遺伝的差異が固定するような二分化が起きるのではないか、もしそうなら放置するのは危険ではないかと述べた。知能の遺伝という考えがアプリオリに拒絶されていた時代にあって、彼らの焦点は遺伝的差異を克服する方策であったにもかかわらず、知能が遺伝的に「決定」されると主張して差別を正当化しようとしている、と批判を浴びた。
カリフォルニア大学ロサンゼルス校ラスキン公共政策大学院の研究者 JISUNG PARK の研究で、2001年から2014年までの13年間、1000万人のアメリカ人学生に行われたPSAT試験の追跡調査が行われた。その結果、気温が高い年の試験結果が悪くなる傾向がみられた。とくに空調の恩恵を受けられない貧困家庭などに大きな影響がみられた[146]。
一部の研究は、多くの研究が、ピークの収入能力や教育レベルにすら達していない若い成人に基づいているため、IQが収入の変動の6分の1しか説明していないと主張している。『g因子(英語版)』の568ページで、アーサー・ジェンセン(英語版)は、IQと収入の相関は平均で中程度の0.4(分散の6分の1または16%)だが、年齢とともに関係は強くなり、人々が最大のキャリアの可能性に達する中年でピークに達すると述べている。『A Question of Intelligence』の中で、ダニエル・セリグマン(英語版)は、IQと収入の相関を0.5(分散の25%)と述べている。
また、アメリカの政治学者であるチャールズ・マレー(英語版)は、米国青年パネル調査(National Longitudianl Survey of Youth,NLSY)の調査対象である1979年のコーホート[111]と1997年のコーホート[199]のデータを基にして、対象者が25歳に達した年の白人の学歴別平均IQの表を作成した[200]。
Hunt 2011, p.5 "As mental testing expanded to the evaluation of adolescents and adults, however, there was a need for a measure of intelligence that did not depend upon mental age. Accordingly the intelligence quotient (IQ) was developed.... The narrow definition of IQ is a score on an intelligence test... where 'average' intelligence, that is the median level of performance on an intelligence test, receives a score of 100, and other scores are assigned so that the scores are distributed normally about 100, with a standard deviation of 15. Some of the implications are that: 1. Approximately two-thirds of all scores lie between 85 and 115. 2. Five percent (1/20) of all scores are above 125, and one percent (1/100) are above 135. Similarly, five percent are below 75 and one percent below 65."
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Terman 1916, p.79 "What do the above IQ's imply in such terms as feeble-mindedness, border-line intelligence, dullness, normality, superior intelligence, genius, etc.? When we use these terms two facts must be born in mind: (1) That the boundary lines between such groups are absolutely arbitrary, a matter of definition only; and (2) that the individuals comprising one of the groups do not make up a homogeneous type."
Wechsler 1939, p.37 "The earliest classifications of intelligence were very rough ones. To a large extent they were practical attempts to define various patterns of behavior in medical-legal terms."
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Truch, Steve (1993). The WISC-III Companion: A Guide to Interpretation and Educational Intervention. Austin, TX: Pro-Ed. p.35. ISBN978-0-89079-585-9. An IQ score is not an equal-interval score, as is evident in Table A.4 in the WISC-III manual.
Bartholomew, David J. (2004). Measuring Intelligence: Facts and Fallacies. Cambridge: Cambridge University Press. p.50. ISBN978-0-521-54478-8. When we come to quantities like IQ or g, as we are presently able to measure them, we shall see later that we have an even lower level of measurement—an ordinal level. This means that the numbers we assign to individuals can only be used to rank them—the number tells us where the individual comes in the rank order and nothing else.
Mackintosh 1998, pp.30–31 "In the jargon of psychological measurement theory, IQ is an ordinal scale, where we are simply rank-ordering people. ... It is not even appropriate to claim that the 10-point difference between IQ scores of 110 and 100 is the same as the 10-point difference between IQs of 160 and 150"
Kaufman, Alan S.; Raiford, Susan Engi; Coalson, Diane L. (2016). Intelligent testing with the WISC-V. Hoboken, NJ: Wiley. pp.683–702. ISBN978-1-118-58923-6. 表4.1の信頼性推定値と表4.4の測定の標準誤差は、一時的な誤差、実施上の誤差、採点上の誤差(Hanna, Bradley, & Holen, 1981)など、臨床評価でテストスコアに影響を与える他の主要な誤差源を考慮していないため、最良の推定値と見なすべきである。考慮すべきもう1つの要因は、下位検査のスコアが、階層的な一般知能因子によって真のスコア分散の一部を反映している程度と、特定の集団因子によって分散を反映している程度である。これらの真のスコア分散の源は混同されているためである。
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