Claims

Social sciences content is positively correlated with perceived ethnic bias in text-based learning materials

Claim · All claims
Evidence · 1 study · associational r1 · q2 · i1 small
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.

q2 i1 The contextual feature disc social (social sciences discipline) showed a statistically significant positive correlation with the bias score (r = 0.163, p = 0.002). → Josmario Albuquerque 2026

Evidence

Josmario Albuquerque 2026

Josmario Albuquerque, Bart Rienties, Martin Hlosta, Wayne Holmes. (2026). Learning Analytics to Uncover Ethnic Bias in Educational Texts: An Ensemble Learning Approach. Journal of Learning Analytics 13(1). https://doi.org/10.18608/jla.2026.8905

q2 · i1 · associational · r1

Correlation analysis (Pearson with Benjamini–Hochberg correction) of features against the bias score in the 345-sentence OER dataset; the Table 6 row for disc social reports t = 3.069, p = 0.002, r = 0.163, 95% CI [0.059, 0.264], a "statistically significant" positive correlation.

"context disc social 3.0690.002 0.0150.163 0.059 0.264"

Discussion

Page metadata
Field Value
type claim
id social-sciences-content-correlates-ethnic-bias
title Social sciences content is positively correlated with perceived ethnic bias in text-based learning materials
description Social sciences content is positively correlated with perceived ethnic bias in text-based learning materials
status review
evidence_strength moderate
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-09
trust unverified — no one has confirmed this page's content
sources 1 — josmario-albuquerque-2026

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