HVG-ACHQ: French Caribbean and Saint Pierre & Miquelon

Although my colleagues are international, their research predominantly focuses on differences within the USA, a tendency I find perplexing. Years ago, at an LCI conference, a British colleague asserted that further research on ethnic or racial differences was unnecessary, claiming the matter was settled. Yet, within a year, he contacted me seeking data on the performance of various ethnic groups in the UK. Similarly, a French colleague, whose work almost exclusively examines differences in the USA, argued that such data was unavailable in France. However, after just ten minutes of searching, I located several French government reports detailing the performance of first- and second-generation immigrants by region of origin. Evidently, he didn’t try too hard. In my view, a logical approach, if one were to pursue this topic seriously, would involve first collecting a broad international dataset—potentially requiring effort such as submitting freedom of information requests—then identifying patterns, and finally hypothesizing about possible causes. After all, the USA is not the world, and we should not assume it reflects global trends. The lack of such comprehensive data is why I remain largely agnostic about the existence of worldwide race differences in cognitive ability, and even more so about their causes

.  .  .

France governs three overseas departments in the Americas—French Guiana, Guadeloupe, and Martinique—along with three overseas American collectivities: Saint Barthélemy (St. Barth), Saint Martin, and Saint Pierre and Miquelon. The populations of these territories display a rich diversity of ancestries, making them an interesting case study.

Saint Pierre and Miquelon, located off the coast of Canada, has a population of approximately 5,819 and is the most European-influenced of France’s overseas territories. Its residents are primarily descendants of French settlers from Normandy, Brittany, and other regions, supplemented by recent migrants from metropolitan France. Saint Barthélemy, a small Caribbean island that separated from Guadeloupe in 2007, has a population of around 10,000. Although France does not officially collect ethnic or racial data, visual observations of children in local primary schools and at festivals suggest the population is roughly 80% of European ancestry (mostly French), 15% of African ancestry, and 5% of other origins. This aligns with historical settlement records, which indicate a majority of French descent.

Figure 1. School and Festival Pictures from St. Barts

Guadeloupe and Martinique are primarily inhabited by admixed Afro-European populations, with additional contributions from descendants of South Asian Indian groups. A 2019 study by Mendisco et al. analyzed mtDNA and Y-DNA haplogroups from individuals whose grandparents were all born in Guadeloupe, estimating ancestry proportions. Averaging these maternal and paternal markers suggests that Guadeloupe’s population is approximately 25.5% European, 69% African, 0.25% Amerindian, and 5.3% other (mostly South Asian). These estimates, which do not account for recent immigration, reflect higher African maternal ancestry and greater European paternal contributions, consistent with the region’s colonial history. Given Martinique’s similar historical trajectory, its ancestry composition is likely comparable, though slight variations may arise from local differences in settlement and immigration patterns.

Notably, island-wide studies on sickle cell anemia suggest that both Guadeloupe and Martinique have lower levels of African ancestry compared to Anglo-Caribbean countries such as Jamaica, Saint Vincent and the Grenadines, Grenada, St. Lucia, and Tobago (Knight-Madden et al., 2019). As shown in Table 1, beta-S and beta-C gene frequencies—markers associated with African ancestry—are approximately 75% of the rates found in these other islands. Extrapolating from these figures suggests a somewhat lower African ancestry proportion of around 60%, since these other countries have around 80% African ancestry (when taking into account admixture in the respective Afro-Caribbean populations and the proportion of non-Afro-Caribbeans).  However, due to the potential influence of genetic drift and selection on specific gene frequencies, the estimates based on Mendisco et al. (2019) remain the most reliable for these populations.

Table 1. Frequency Data on Sickle Cell-Related Alleles (β^S and β^C) by Country/Territory

Country/Territory	β^S	β^C	β^S + β^C
Jamaica	0.055	0.019	0.074
Guadeloupe	0.042	0.012	0.054
Martinique	0.04	0.011	0.051
French Guiana	0.04	0.011	0.051
Tobago	0.051	0.02	0.071
Grenada	0.054	0.017	0.071
Saint Lucia	0.06	0.012	0.072
Haiti	0.062	0.012	0.074
Saint Vincent & Grenadines	0.055	0.015	0.07
Cuba	0.011	0.003	0.014

Comprehensive admixture data for Saint Martin, a French overseas collectivity populated by admixed Afro-Caribbean groups, is limited. However, a study by Bera et al. (2001) examined HLA class I and II allele frequencies, revealing a population predominantly of African ancestry with a minor European component and no significant contributions from other groups. Based on this and comparisons with nearby islands like St. Kitts and Nevis, a rough estimate of Saint Martin’s ancestry might be approximately 80% African and 20% European, though this remains an approximation pending more detailed genetic analysis.

Figure 2. Festival Pictures from St. Martin

The majority of French Guiana’s population is comprised of recent immigrants and their descendants from countries such as Guyana, Suriname, Brazil, Haiti, China, Laos, Saint Lucia, and metropolitan France. The remainder includes Amerindians, Caribbean Creoles, and Maroons. Genetic studies suggest that the Maroons (Fortes-Lima et al., 2017), East Asians (Brucato et al., 2012), and Amerindians (Mazières et al., 2009) of this department exhibit little admixture. However, no genetic data is available for the Creole populations. Population admixture can be approximated by weighting ethnic or national groups according to their reported average ancestry; though official ethnic data is not collected in French Guiana various sources have reported estimates. The percentages provided, as detailed in Table 2, are plausible estimates.

Table 2: Admixture Estimates for French Guiana

	% Pop	African %	European %	Amerindian %	Other %
Maroon	15	98.00	2.00	0.00	0.00
Creole	25	80.00	20.00	0.00	0.00
Amerindian	3	0.68	9.56	89.76	0.00
Guyana	6	35.00	5.00	10.00	50.00
Suriname	12.5	40.00	5.00	5.00	50.00
Brazilian	9.3	19.60	68.10	11.60	0.00
Haitian	9.2	94.00	6.00	0.00	0.00
Chinese	3	0.00	0.00	0.00	100.00
Laotian	2	0.00	0.00	0.00	100.00
St. Lucian	3	71.67	18.22	7.22	2.90
Metro. French	12	2.83	87.20	0.00	9.97
Weighted Ave.	100	54.78	24.41	5.21	15.53

France is becoming increasingly less European in its demographic composition. Although ethnicity is not officially reported, detailed data on first- to third-generation immigrants by region of origin is available (INSEE, 2024). By combining this data with estimates of its overseas territories, admixture estimates can be derived for France as a whole. These estimates reveal a growing proportion of the population with North African and Middle Eastern ancestry, categorized here as “other.” The demographic shift, often described as the replacement of the indigenous French population, is substantially more pronounced among younger age groups, a trend partially obscured in overall population estimates. Admixture estimates for both France as a whole and its overseas departments and territories in the Americas are summarized in Table 3.

Table 3: Admixture Estimates for France and French American Possessions

Country	Population	African %	European %	Amerindian %	Other %
France*	68,373,647	4.97	84.67	0.00	10.36
French Guiana	292354	54.78	24.41	5.21	15.53
Guadeloupe	378561	69.00	25.50	0.25	5.30
Martinique	349,925	69.00	25.50	0.25	5.30
St. Barth	10,967	15.00	80.00	0.00	5.00
St. Martin	32489	80.00	20.00	0.00	0.00
St. Pierre et Miquelon	5819	0.00	100.00	0.00	0.00

*Including overseas France; North Africans included as “Other.”

Since the 2017–2018 school year, France has administered yearly academic achievement tests to sixth and tenth graders, with assessments later expanded to other grades. The language test evaluates reading comprehension, oral language, spelling, grammar, and vocabulary, while the math test assesses knowledge of numbers, computation, problem-solving, geometry, and measurements. As of the time of writing, means and standard deviations were available for sixth-grade tests (2017–2023) and tenth-grade tests (2019–2024) for French Guiana, Guadeloupe, and Martinique.

Additionally, since 1998, the Journée Défense et Citoyenneté (JDC) has required citizens aged 16–25 to take language comprehension tests, which include tests of word recognition and passage comprehension. Percentages of individuals facing difficulties are reported by department. We converted these rates for 2014–15, 2018–19, 2019–20, and 2022–23 into d-scores. Data was available for French Guiana, Guadeloupe, and Martinique.  These test scores have been shown to correlate at r = .54 with a 66-item math test (Herrero et al., 2015). Although this correlation is substantially lower than the r = .85 found for PIAAC, it is relatively close to the r = .65 typically observed for academic achievement tests, such as the American NAEP tests.

Due to their smaller populations, data for Saint Pierre and Miquelon, Saint Barthélemy, and Saint Martin are less comprehensive, resulting in less precise estimates. Thus, for Saint Pierre and Miquelon, we additionally computed scores using all available data points, while for Saint Martin and Saint Barthélemy, we calculated results additionally for grade 4. These findings are presented in Tables 4 and 5 below, respectively.

Table 4. Tests Scores for Saint Pierre & Miquelon

		Language			Math
Year	Grade	France	SP&M		France	SP&M
		% Satisfactory	% Satisfactory	d	% Satisfactory	% Satisfactory	d	Ave. d
2023	Cours Préparatoire	78.90	76.10	0.09	81.60	74.00	0.26	0.18
2023	Cours Élémentaire 1	77.40	85.30	-0.30	68.00	76.80	-0.26	-0.28
2023	Cours Moyen 1	64.30	57.60	0.17	56.60	56.30	0.01	0.09
2024	Cours Moyen 2			0.16			0.01	0.09
2019	Middle school			-0.10			-0.31	-0.21
2023	Middle school			0.13			0.11	0.12
2023	Middle school	52.90	44.80	0.20	47.10	41.90	0.13	0.17
2019	Middle school			-0.10			-0.17	-0.14
2022	Vocational School	55.00	81.00	-0.75	31.00	42.00	-0.29	-0.52
2022	College Prep.	92.00	95.00	-0.24	77.00	84.00	-0.26	-0.25

Table 5. Test Scores for Saint Barthélemy and Saint Martin

		Language		Math		Average
		d France / St. Martin	d France / St. Barts	d France / Martin	d France / St. Bars	d France / Martin	d France / St. Barts	d France / St. Barts
6eme	2019	0.94	-0.06	1.16	0.36	1.05	0.15	0.15
6eme	2020	1.36	-0.02	1.00	-0.47	1.18	-0.24	-0.24
6eme	2021	1.34	-0.23	1.12	-0.24	1.23	-0.23	-0.23
6eme	2022	1.16	0.29	1.03	0.27	1.09	0.28	0.28
ave						1.14	-0.01	-0.01
CE1	2019	0.95	0.15	0.65	0.23	0.80	0.19	0.19
CE1	2020	1.10	-0.01	0.68	0.07	0.89	0.03	0.03
CE1	2021	1.24	0.21	0.66	0.04	0.95	0.13	0.13
CE1	2022	1.13	-0.07	0.71	-0.06	0.92	-0.07	-0.07
ave						0.89	0.07	0.07
Grade 10 tech (LEGT R. Weinum & 2nde M. Choisy)	2022	0.87	0.25	0.40	-0.63	0.63	-0.19	-0.19
Grade 10 prof (LP D. Jeffry & 2nde M. Choisy)	2022	0.98	0.81	0.32	-0.61	0.65	0.10	0.10
ave						0.64	-0.04	-0.04

For consistency, we rely on averages from sixth and tenth grades across these three collectivities, despite having only one year of tenth-grade data for Saint Martin, which was derived from a single school.  For the overseas departments we averaged Grade 6, Grade 10, and the DofL test values. Results, alongside Human Development Index (HDI) and socioeconomic status (SES) data when available, are presented in Table 6 below. Academic achievement (ACHQ) and SES/HDI correlated strongly, with r-values ranging from .90 to .95, for regions with data. For the 13 Metropolitan French regions (that is, excluding overseas possessions) Grade 6 Math and Reading scores correlated at r = .69 with DofL scores, providing further support for the validity of the latter as measures of academic achievement.

Table 6. Test Scores, HDI, and S-factor for French Regions and Territories

Region	Grade_6_ACH	Grade_10_ACH	DofL_ACH	ACH_ave	ACHQ	S-factor	HDI
National	0.000	0.000	0.000	0.000	99.28		0.886
Auvergne-rhone-alpes	-0.101		-0.142	-0.121	101.10	0.727	0.881
Bourgogne-franche-comte	-0.026		0.012	-0.007	99.39	0.606	0.863
Bretagne	-0.138		-0.162	-0.150	101.53	0.725	0.879
Centre-val de loire	0.008		0.039	0.024	98.93	0.683	0.865
Corse	0.059	0.210	-0.112	-0.026	99.68	-0.17	0.843
Grand-est	-0.002		-0.033	-0.017	99.54	0.528	0.867
Hauts-de-france	0.137		0.036	0.087	97.98	0.294	0.852
Ile-de-france	-0.069		-0.147	-0.108	100.90	0.708	0.93
Normandie	0.079	0.045	0.005	0.042	98.65	0.537	0.864
Nouvelle-aquitaine	-0.047		-0.043	-0.045	99.95	0.68	0.872
Occitanie	-0.032		-0.049	-0.041	99.89	0.539	0.881
Pays de la loire	-0.079		-0.115	-0.097	100.74	0.765	0.88
Provence-alpes-cote d'azur	0.004		-0.090	-0.043	99.92	0.391	0.883
Guadeloupe	0.460	0.565	0.700	0.575	90.66	-1.194	0.841
French Guyane	1.009	0.935	1.200	1.048	83.56	-2.325	0.787
Martinique	0.372	0.458	0.700	0.510	91.63	-0.645	0.851
Mayotte	1.496	1.589	1.800	1.628	74.86	-2.176	0.764
La Reunion	0.342	0.361	0.600	0.434	92.77	-0.674	0.829
St-Pierre et Miquelon	-0.060	-0.14		-0.100	100.78
St. Martin	1.140	0.64		0.890	85.93
St. Barthélemy	-0.01	-0.04		-0.025	99.66

Overseas departments and territories with less European influence tend to exhibit lower academic performance. This trend is holds when also considering the predominantly African population of Mayotte (Msaidie et al., 2011), the Afro-European-South Asian demographic mix of La Réunion (Berniell-Lee et al., 2008), and French Polynesia (not shown). However, the predominantly African Caribbean departments of Guadeloupe and Martinique demonstrate unexpectedly strong academic performance.  The true ACHQ scores may even be higher insofar as JDC tests may be linguistically biased. However, that Guadeloupéens and Martiniquais do relatively better on the grade 6 and 10 language tests, which include an oral comprehension test, than the math tests would argue against linguistic bias. However, formal testing would be required to conclusively rule out any such bias.

While this analysis primarily focuses on achievement tests, findings from a study on IQ in the Guadeloupe population present a more complex picture. Oulhote et al. (2023) reported Raven’s Matrices scores for mothers and French-WISC scores for children from the TIMOUN mother-child cohort in Guadeloupe. The study involved 1,068 pregnant women recruited from the general population between November 2004 and December 2007, with a follow-up seven years later. Among the 569 children aged 7-8, the average WISC-IV score was 87.1 relative to the French mean. The 541 mothers achieved an average Standard Progressive Matrices (SPM) score of 35.4, equivalent to an Advanced Progressive Matrices (APM) score of 5.62 and an IQ of 70.79 based on British 1992 norms. Adjusted for the Flynn effect, this drops to 67.43. Averaging these scores yields a HVGIQ of 77 for Guadeloupe, which would need to be adjusted upwards a few points to align with U.S. metrics.

Jason Malloy also reported a low Raven’s Matrices score (IQ = 77, relative to the UK mean) for Guadeloupe, based on Massina et al. (2000). However, the Raven’s IQ scores are inconsistent with achievement test data, suggesting they may not accurately reflect the general cognitive ability of the population. Regardless, this series emphasizes academic achievement, which may diverge from nonverbal intelligence measures due to variations in schooling quality. This is evident in cases like Argentina, where achievement test scores are over 15 points lower than intelligence test scores.

Datafile, with sources.

References

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