معدل الذكاء وعدم المساواة العالمية

IQ and Global Inequality

معدل الذكاء والعالمية وعدم المساواة العالمية كتاب الدكتور ريتشارد لين 2006 الأستاذ الفخري لفهم النفس في جامعة أولستر في أيرلندا الشمالية والدكتور فانهانين الأستاذ الفخري في العلوم السياسية في جامعة تامبيري معدل الذكاء والعالمية لعدم المساواة هومتابعة لكتاب 2002 معدل الذكاء

معدل الذكاء الوطني والتنمية الاقتصادية

مؤشر جودة الأحوال البشرية

مؤشر (QHC) لرتشارد لين.

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The quality of human conditions (QHC) index was computed from five variables.

purchasing power parity Gross National Income (PPP-GNI) per capita 2002
adult literacy rate 2002
gross tertiary enrollment ratio
life expectancy at birth 2002
مستوى الدمقرطة 2002 (مؤشر الديمقراطية من تاتوڤانهانن)

Values of the index range from 10.7 (Burkina Faso) to 89 (Norway). Lynn and Vanhanen write that they would have preferred to include a sixth measure, an indicator of income inequality, but that statistical data for that variable was not available for all countries. They write that the QHC index differs significantly from other widely used indexes (such as the Human Development Index) in that QHC also measures democratization. Some of their claims have been received support in a 2007 study by Rindermann.

All countries	Estimate IQ (79 countries)	Total (192 countries)
QHC	0.805	0.725	0.791
PPP GNI per capita 2002	0.693	0.342	0.616
Adult literacy rate 2002	0.642	0.655	0.655
Tertiary enrollment ratio	0.746	0.699	0.745
Life expectancy at birth 2002	0.765	0.690	0.750
Index of Democratization 2002	0.569	0.322	0.530
Excluding smallest countries	Calculated IQ (98 countries)	Estimate IQ (62 countries)	Total (160 countries)
QHC	0.846	0.800	0.839
PPP GNI per capita 2002	0.739	0.266	0.649
Adult literacy rate 2002	0.710	0.746	0.733
Tertiary enrollment ratio	0.778	0.734	0.780
Life expectancy at birth 2002	0.833	0.753	0.817
Index of Democratization 2002	0.598	0.408	0.584

غير ذلك من التدابير على الصعيد العالمي وعدم المساواة

The relationship of national IQ to twelve other measures of global inequality were examined.

Human Development Index (HDI)
Gender-related Development Index (GDI)
Economic growth rate (EGR)
Gini index of inequality in income or consumption (Gini)
Population below $2 a day international poverty line (Poverty)
Measures of undernourishment (PUN)
Maternal mortality ratio (MMR) and infant mortality rate (IMR)
Corruption Perceptions Index (CPI)
Economic freedom ratings (EFR)
the Index of Economic Freedom (IEF)
Population pyramids (MU-index)
Human happiness and life-satisfaction.

All twelve measures of global inequality are significantly correlated with the QHC index. According to the book, eleven of the twelve measures are significantly correlated with national IQ. The measures of human happiness and life satisfaction are not significantly correlated with national IQ.

Correlations	IQ	QHC
HDI	0.776	0.940
GDI	0.849	0.951
EGR 3	0.747	0.840
EGR 4	0.709	0.871
Gini	-0.538	-0.464
Poverty	-0.653	-0.799
PUN 1	-0.500	-0.648
MMR	-0.730	-0.759
IMR	-0.771	-0.861
CPI	0.591	0.762
EFR	0.606	0.674
IEF	0.418	0.620
MU-index	0.806	0.902
Happiness	0.029	0.315
Life satisfaction	0.033	0.396

خط العرض ودرجة الحرارة

ارتباط	خط العرض	درجة الحرارة
Degrees latitude	1	-0.885
Annual mean temperature	-0.885	1
National IQ	0.677	-0.632
QHC	0.659	-0.562
PPP GNI per capita 2002	0.528	-0.407
Adult literacy rate 2002	0.482	-0.467
Tertiary enrollment ratio	0.718	-0.649
Life expectancy at birth 2002	0.505	-0.379
Index of Democratization 2002	0.512	-0.460

معدل الذكاء الوطنية والقيم

Calculated and estimated national average IQ according to book.

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البلد/المنطقة	IQ (2002)	IQ (2006)	PPP-GNI per capita 2002	QHC
هونگ كونگ	107	108	27,490	60.8
سنغافورة	103	108	23,730	60.7
كوريا الشمالية	105*	106*	1,000	38
كوريا الجنوبية	106	106	16,960	75.4
اليابان	105	105	27,380	71.4
الصين	100	105	4,520	39.7
تايوان	104	105	23,400	79.4
إيطاليا	102	102	26,170	78.9
آيسلندا	98*	101	29,240	80
منغوليا	98*	101*	1,710	48.1
سويسرا	101	101	31,840	82.2
النمسا	102	100	28,910	80.7
لوكسمبورگ	101*	100*	53,230	76.4
هولندا	102	100	28,350	82.8
النرويج	98	100	36,690	89
المملكة المتحدة	100	100	26,580	76.7
بلجيكا	100	99	28,130	84.1
كندا	97	99	28,930	77.8
إستونيا	97*	99	11,630	64.5
فنلندا	97	99	26,160	85.1
ألمانيا	102	99	26,980	78
نيوزيلندا	100	99	20,550	76.2
پولندا	99	99	10,450	62.7
السويد	101	99	25,820	82.9
أندورا	N/A	98*	19,000	58.7
أستراليا	98	98	27,440	82.8
التشيك	97	98	14,920	64.5
الدنمارك	98	98	30,600	85.4
فرنسا	98	98	27,040	78.1
المجر	99	98	13,070	64.1
لاتڤيا	97*	98*	9,190	65.5
إسپانيا	97	98	21,910	75.8
الولايات المتحدة	98	98	36,120	86.6
بلاروس	96*	97*	5,500	57.2
مالطا	95*	97	17,710	66.4
روسيا	96	97	8,080	64.5
أوكرانيا	96*	97*	4,800	61.8
مولدوڤا	95*	96*	1,600	46.2
سلوڤاكيا	96	96	12,590	63.2
أوروگواي	96	96	7,710	64
إسرائيل	94	95	19,000	75.3
الپرتغال	95	95	17,820	67
أرمنيا	93*	94*	3,230	50.2
جورجيا	93*	94*	2,270	51.2
قزخستان	93*	94*	5,630	49
رومانيا	94	94	6,490	53
ڤيتنام	96*	94	2,300	39.5
الأرجنتين	96	93	10,190	64.7
بلغاريا	93	93	7,030	59.1
اليونان	92	92	18,770	76.1
ماليزيا	92	92	29,570	78.5
أيرلندا	93	92	8,500	52.1
بروناي	92*	91*	19,210	50.8
كمبوديا	89*	91*	1,970	28.6
قبرص	92*	91*	18,650	67.6
لتوانيا	97*	91	10,190	65.4
جمهورية مقدونيا	93*	91*	6,420	54.4
تايلند	91	91	6,890	50.3
ألبانيا	90*	90*	4,960	51.2
برمودا	N/A	90	36,000	75.8
البوسنة والهرسك	N/A	90*	5,800	51.4
تشيلي	93*	90	9,420	59.5
كرواتيا	90	90	10,000	61.7
قيرغيزستان	87*	90*	1,560	48.1
هجريا	90	90	6,300	50.2
المكسيك	87	90	12,500	52.9
جزر كوك	N/A	89	5,000	45.7
كوستاريكا	91*	89*	8,650	53.7
لاوس	89*	89	1,660	24.9
موريشيوس	81*	89	10,820	52.2
سورينام	89	89	6,590	50.6
الإكوادور	80	88	3,340	47.4
ساموا	87	88	5,570	49.7
أذربيجان	87*	87*	3,010	47.2
بوليڤيا	85*	87	2,390	49.7
البرازيل	87	87	7,450	51.1
تيمور الشرقية	N/A	87*	3,940	46.7
گويانا	84*	87*	3,070	40.2
إندونيسيا	89	87	1,600	28.1
العراق	87	87	1,027	30.7
ميانمار	86*	87*	930	42.4
طاجيكستان	87*	87*	1,640	27.5
هجرمنستان	87*	87*	4,780	41.7
اوزبكستان	87*	87*	1,640	39.4
الكويت	83*	86	17,780	49.9
الفلپين	86	86	4,450	51.6
سيشل	81*	86*	18,232	60.6
تونگا	87	86	6,820	40.5
كوبا	85	85	5,259	46.2
فيجي	84	85	5,330	51.9
كيريباس	84*	85*	800	37.1
كاليدونيا الجديدة	N/A	85	21,960	54.9
پيرو	90	85	4,880	49.2
ترنيداد وتوباگو	80*	85*	9,000	52
اليمن	83*	85	800	24.5
أفغانستان	83*	84*	700	13.2
بليز	83*	84*	15,960	56.1
كولومبيا	88	84	5,490	44.2
ميكرونزيا	84*	84*	6,150	48.4
إيران	84	84	6,690	40.2
الأردن	87*	84	4,180	43.4
جزر مارشال	84	84	1,600	44.2
المغرب	85	84	2,000	39.9
پاكستان	81*	84	3,730	31.7
پنما	84*	84*	1,960	26.2
پاراگواي	85*	84	6,060	56.6
پورتوريكو	84	84	4,590	45.2
السعودية	83*	84*	15,800	63.6
جزر سولومون	84*	84*	12,660	44.1
البهاما	78*	84*	1,590	41.5
الإمارات العربية المتحدة	83*	84*	24,030	48.8
ڤانواتو	84*	84*	2,850	31.4
ڤنزويلا	88*	84	5,220	47.4
الجزائر	84*	83*	5,530	39.9
البحرين	83*	83*	16,190	49.3
ليبيا	84*	83*	7,570	49.3
عُمان	83*	83*	13,000	40.6
پاپوا غينيا الجديدة	84*	83	2,180	38.4
سوريا	87*	83	5,348	38.9
تونس	84*	83*	6,440	40.6
بنگلادش	81*	82*	1,720	29.8
جمهورية الدومنيكان	84*	82	6,270	46.8
الهند	81	82	2,650	36.3
لبنان	86	82	4,600	55.8
مدغشقر	79*	82	730	28.6
مصر	83	81	3,810	37.3
هندوراس	84*	81	2,540	41.9
المالديڤ	81*	81*	4,798	38.5
نيكاراگوا	84*	81*	2,350	41.3
جزر ماريانا الشمالية	N/A	81	12,500	51.3
بربادوس	78	80	14,660	60.9
بوتان	78*	80*	1,969	24.1
السلڤادور	84*	80*	4,790	42.6
گواتيمالا	79	79	4,040	34.6
سريلانكا	81*	79	3,510	47.7
نيپال	78	78	1,370	26.9
قطر	78	78	19,844	45.6
جزر القمر	79*	77*	1,640	24.6
الرأس الأخضر	78*	76*	4,920	40.5
موريتانيا	73*	76*	1,790	20.5
أوغندا	73	73	1,360	25.4
كنيا	72	72	1,010	27.3
جنوب أفريقيا	72	72	9,810	38.3
تنزانيا	72	72	580	23.2
غانا	71	71	2,080	33.7
گرينادا	75*	71*	6,600	45.3
جامايكا	72	71	3,680	46.5
سانت ڤنسنت والگرنادينز	75*	71	5,190	48.4
السودان	72	71	1,740	24.6
زامبيا	77	71	800	21.8
أنتيگا وبربودا	75*	70*	10,390	53.2
بنين	69*	70*	1,060	20.5
بتسوانا	72*	70*	7,740	29.4
ناميبيا	72*	70*	6,880	31.1
رواندا	70*	70*	1,260	18.5
توگو	69*	70*	1,450	26
بوروندي	70*	69*	630	15.2
ساحل العاج	71*	69*	1,450	18.1
ملاوي	71*	69*	570	24.3
مالي	68*	69*	840	13.4
النيجر	67*	69*	800	13.5
نيجريا	67	69	800	27.3
أنگولا	69*	68*	1,840	13.7
بوركينا فاسو	66*	68*	1,090	10.7
تشاد	72*	68*	1,010	20.4
جيبوتي	68*	68*	2,040	22
إرتريا	68*	68*	1,040	21.4
الصومال	68*	68*	500	15.2
سوازيلاند	72*	68*	4,730	22.2
دومنيكا	75*	67	4,960	48.8
غينيا	63	67	2,060	22.5
غينيا-بيساو	63*	67*	680	20.3
هايتي	72*	67*	1,610	20.4
لسوتو	72*	67*	2,970	24.3
ليبريا	64*	67*	1,000	21.2
سانت كيتس ونڤيس	75*	67*	10,750	45.5
ساوتومه وپرنسيپه	59*	67*	1,317	37.9
السنغال	64*	66*	1,660	20.7
گامبيا	64*	66*	1,540	21.3
زيمبابوي	66	66	2,180	25.2
الكونغو	73	65	630	17.9
الكاميرون	70*	64	1,910	23.1
جمهورية أفريقيا الوسطى	68*	64	1,170	19.1
الكونغوالديمقراطية	65	64	700	26.9
إثيوپيا	63	64	780	16.7
الگابون	66*	64*	5,530	32.2
موزمبيق	72*	64	990	18
سيراليون	64	64	500	13.8
سانت لوشيا	75*	62	4,950	51.1
غينيا الإستوائية	59	59	9,100	30.4
"" Denotes estimated National IQ PPP-GNI = purchasing power parity gross national income. QHC = is a composite index called quality of human conditions*.

نقد

Hunt and Wittmann (2008) write of Lynn’s IQ data:

The majority of the data points were based upon convenience rather than representative samples. Some points were not even based on residents of the country. For instance, the “data point for Suriname was based on tests given to Surinamese who had migrated to the Netherlands, and the “data point” for Ethiopia was based on the IQ scores of a highly selected group that had emigrated to Israel and, for cultural and historical reasons was hardly representative of the Ethiopian population. The data point for Mexico was based on a weighted averaging of the results of a study of “Native American and Mestizo children in Southern Mexico” with result of a study of residents of الأرجنتين .

Upon reading the original reference, they found that the “data point” that Lynn and Vanhanen used for the lowest IQ estimate, Equatorial Guinea, was actually the mean IQ of a group of Spanish children in a home for the developmentally disabled in Spain. Corrections were applied to adjust for differences in IQ cohorts (the “Flynn” effect) on the assumption that the same correction could be applied internationally, without regard to the cultural or economic development level of the country involved. While there appears to be rather little evidence on cohort effect upon IQ across the developing countries, one study in Kenya (Daley, Whaley, Sigman, Espinosa, & Neumann, 2003) shows a substantially larger cohort effect than is reported for developed countries (p.?)

Crawford-Nutt (1976) found that African black students enrolled in westernized schools scored higher on progressive matrix tests than did American white students. The study was meant to examine perceptual/cultural differences between groups, and demonstrated that one’s performance on western standardized tests correspond more closely with the quality and style of schooling that one receives more so than other factors . Buj (1981) showed Ghanaian adults to score higher on a supposedly ‘culture fair’ IQ test than did Irish adults; scores were 80 (Ghanaian) and 78 (Irish), respectively . Shuttleworth-Edwards et al. (2004) conducted a study with black South Africans between the ages of 19–30, where highly significant effects for both level and quality of education within groups whose first language was an indigenous black African language, was revealed. Black African first language groups (as well as white English speaking groups) with advantaged education were comparable with the US standardization in IQ test scores (e.g. WAIS-III).

انظر أيضاً

ناشري خط

Washington Summit Publishers

Theories of Race and Intelligence:

Cattell Culture Fair III
Evolution of human intelligence
Flynn effect
Fluid and crystallized intelligence
General intelligence factor
Gini coefficient
Hominid intelligence
Intelligence and public policy
Race and intelligence

مطبوعات عن الذكاء:

IQ and the Wealth of Nations
IQ and Global Inequality
The Mismeasure of Man
Race Differences in Intelligence

نظريات روابط:

Brain to body mass ratio
Height and intelligence
Neuroscience and intelligence
Sex and intelligence

وصلات خارجية

Lynns posting of a favorable review that characterizes the 006 work as a reply to criticisms of their earlier results
A site critical of Lynn;s claims
National IQ means, calibrated on the basis of PISA scores and transformed from educational attainment

المصادر

^ Rindermann, Heiner: The g-factor of international cognitive ability comparisons: the homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality 21 (2007) 667-706 [1]
^ خطأ استشهاد: وسم <ref> غير سليم؛ لا نص تم توفيره للمراجع المسماة IQWN
^ خطأ استشهاد: وسم <ref> غير سليم؛ لا نص تم توفيره للمراجع المسماة IQGI
^ Hunt, E. & Wittmann, W. (2008). National intelligence and prosperity. Intelligence. Vol. 36, 1, January-February pp. 1-9.
^ Hunt, E. & Wittmann, W. (2008). National intelligence and prosperity. Intelligence. Vol. 36, 1, January-February pp. 1-9.
^ Crawford-Nutt. D. (1976). Are black scores on Raven’s Standard Progressive Matrices an artifact of method of test presentation? Psychologia Africana, 16, 201-206
^ Buj, V. (1981). "Average IQ values in various European countries." Personality and Individual Differences, 2:168-169
^ Shuttleworth-Edwards A., Kemp R., Rust A., Muirhead J., Hartman N., Radloff S. (2004). Cross-cultural Effects on IQ Test Performance: A Review and Preliminary Normative Indications on WAIS-III Test Performance. Journal of Clinical and Experimental Neuropsychology (Neuropsychology, Developm, Volume 26, Number 7, October 2004 , pp. 903-920(18)