Claims

The male advantage in geometry, broad mathematics, and computation increases across grades, reaching approximately d = 0.541, d = 0.255, and d = 0.207 by the end of secondary schooling, but grade slopes are flat for advanced mathematics, basic numeracy, and national tests

Claim · All claims
Evidence · 1 study (2 entries) · quant-synthesis r2 · q4
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q4 i? The Type of content × Grade interaction significantly improved model fit, with grade a significant positive predictor for broad mathematics (B = 0.015, p < .001), computation (B = 0.014, p = .018), and geometry (B = 0.048, p = .003), but not for advanced mathematics, basic numeracy, or national tests. → Sara Caviola 2026 q4 i? A male advantage in geometry, broad mathematics, and computation emerges around fifth grade and increases through late adolescence, with estimated values of approximately d = 0.541 (Geometry), d = 0.255 (Broad mathematics), and d = 0.207 (Computation) by the end of secondary schooling. → Sara Caviola 2026 (2)

Evidence

Sara Caviola 2026

Sara Caviola, David Giofrè, Enrico Toffalini, Lorenzo Esposito, Irene Tonizzi, David C. Geary. (2026). Sex Differences in Mathematics: A Meta-analytic Review Across Content, Grades, and Geographic Regions. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10125-8

q4 · i? · quant-synthesis · r2

Meta-regression testing the Type of content × Grade interaction on the moderator dataset; model fit improved significantly (χ²(5) = 13.02, p = .023), indicating domain-specific grade slopes. The article reports the per-domain grade coefficients in the quote.

"Grade was a significant positive predictor for Broad mathematics ( B = 0.015, p < .001), Computation (B = 0.014, p = .018), and Geometry (B = 0.048, p = .003), but not for Advanced mathematics, Basic numeracy, or National tests."

Sara Caviola 2026 (2)

Sara Caviola, David Giofrè, Enrico Toffalini, Lorenzo Esposito, Irene Tonizzi, David C. Geary. (2026). Sex Differences in Mathematics: A Meta-analytic Review Across Content, Grades, and Geographic Regions. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10125-8

q4 · i? · quant-synthesis · r2

Estimated marginal means from the Type of content × Grade interaction model, depicted in Fig. 4, showing domain-specific grade trajectories of the male advantage. The article reports the end-of-secondary-schooling estimates in the quote.

"a male advantage in Geometry, Broad mathematics, and Computation emerges around fifth grade and increases through late adolescence, with estimated values of approximately d = 0.541 (Geometry), d = 0.255 (Broad mathematics), and d = 0.207 (Computation) by the end of secondary schooling."

Discussion

Page metadata
Field Value
type claim
id grade-by-content-interaction-sex-differences-mathematics
title The male advantage in geometry, broad mathematics, and computation increases across grades, reaching approximately d = 0.541, d = 0.255, and d = 0.207 by the end of secondary schooling, but grade slopes are flat for advanced mathematics, basic numeracy, and national tests
description The male advantage in geometry, broad mathematics, and computation increases across grades, reaching approximately d = 0.541, d = 0.255, and d = 0.207 by the end of secondary schooling, but grade slopes are flat for a...
status review
evidence_strength moderate
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-21
trust unverified — no one has confirmed this page's content
sources 2 — sara-caviola-2026, sara-caviola-2026-2

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