Reproducibility package for Validation Of A Cross-Linguistic Pictorial Socioeconomic Status Instrument For Illiterate And Diverse Global Populations In The Technological Age

Measuring socioeconomic status (SES) remains a challenge in educational assessment, as text-based instruments often introduce construct-irrelevant variance among low-literacy populations. This study validates a novel pictorial SES instrument designed to mitigate these barriers. Data were collected via a digital app from 1,101 users across three linguistic groups: Bangla (n = 645), French (n = 280), and Zulu (n = 176). Methodologically, multiple nominal pictorial responses were collapsed into binary “Low” and “High” SES levels based on substantive economic meaning to address cross-cultural heterogeneity. Confirmatory factor analysis (CFA) using Weighted Least Squares Mean and Variance Adjusted estimation established a 6-item factor structure with good model fit (χ^2 (9)=4.97,p=0.84, RMSEA = 0.00 [90% CI: 0.00, 0.02], CFI = 1.00, SRMR = 0.03). Mean inter-item tetrachoric correlation (.23) confirmed ideal internal consistency. Nomological validity was supported by a moderate correlation (r = .34) with early literacy skills, consistent with existing educational research. A multiple-group CFA established scalar measurement invariance across all three languages, confirming that the items function equivalently across diverse linguistic backgrounds. Substantively, the validated scale captures the transition to entry-level modernity, distinguishing between levels of poverty through infrastructural access rather than subjective social ranking. By removing the literacy-based barriers inherent in traditional surveys, this low-cost, digitally scalable tool offers a dignity-affirming and methodologically sound mechanism to help ensure accurate representation of economically disadvantaged populations in global educational research.