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No negative Flynn effect in France: Why variations of intelligence should not be assessed using tests based on cultural knowledge

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  • Gonthier, Corentin
  • Grégoire, Jacques
  • Besançon, Maud

Abstract

In 2015, Dutton and Lynn published an account of a decrease of intelligence in France (negative Flynn effect) which had considerable societal impact. This decline was argued to be biological. However, there is good reason to be skeptical of these conclusions. The claim of intelligence decline was based on the finding of lower scores on the WAIS-III (normed in 1999) for a recent sample, but careful examination of the data suggests that this decline was in fact limited to subtests with a strong influence of culture-dependent declarative knowledge. In Study 1, we re-analyzed the data used by Dutton and Lynn (2015) and showed that only subtests of the WAIS primarily assessing cultural knowledge (Gc) demonstrated a significant decline. Study 2 replicated this finding and confirmed that performance was constant on other subtests. An analysis of differential item functioning in the five subtests with a decline showed that about one fourth of all items were significantly more difficult for subjects in a recent sample than in the original normative sample, for an equal level of ability. Decline on a subtest correlated 0.95 with its cultural load. These results confirm that there is currently no evidence for a decrease of intelligence in France, with prior findings being attributable to a drift of item difficulty for older versions of the WAIS, due to cultural changes. This highlights the role of culture in Wechsler's intelligence tests and indicates that when interpreting (negative) Flynn effects, the past should really be treated as a different country.

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  • Gonthier, Corentin & Grégoire, Jacques & Besançon, Maud, 2021. "No negative Flynn effect in France: Why variations of intelligence should not be assessed using tests based on cultural knowledge," Intelligence, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:intell:v:84:y:2021:i:c:s0160289620300908
    DOI: 10.1016/j.intell.2020.101512
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    References listed on IDEAS

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    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Joseph Stauffer & Jorge Mendoza, 2001. "The proper sequence for correcting correlation coefficients for range restriction and unreliability," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 593-594, December.
    3. A. Hakstian & Marsha Schroeder & W. Rogers, 1988. "Inferential procedures for correlation coefficients corrected for attenuation," Psychometrika, Springer;The Psychometric Society, vol. 53(1), pages 27-43, March.
    4. Joseph Stauffer & Jorge Mendoza, 2001. "The proper sequence for correcting correlation coefficients for range restriction and unreliability," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 63-68, March.
    5. Cervantes, Víctor H., 2017. "DFIT: An R Package for Raju's Differential Functioning of Items and Tests Framework," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i05).
    6. Nambury Raju, 1988. "The area between two item characteristic curves," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 495-502, December.
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    Cited by:

    1. Lazaridis, Alexandros & Vetter, Marco & Pietschnig, Jakob, 2022. "Domain-specificity of Flynn effects in the CHC-model: Stratum II test score changes in Germanophone samples (1996–2018)," Intelligence, Elsevier, vol. 95(C).
    2. Gonthier, Corentin & Grégoire, Jacques, 2022. "Flynn effects are biased by differential item functioning over time: A test using overlapping items in Wechsler scales," Intelligence, Elsevier, vol. 95(C).
    3. Egeland, Jonathan, 2022. "The ups and downs of intelligence: The co-occurrence model and its associated research program," Intelligence, Elsevier, vol. 92(C).

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