Standard PCA with Pearson correlations was chosen over polychoric PCA for two reasons: the dataset is predominantly binary and ordinal with limited scale range, and polychoric estimation on 87 variables with n=1,014 introduced instability in the correlation matrix. Polychoric was tested as a robustness check and produced a near-identical factor structure with marginally different loadings, confirming the standard approach was appropriate.

An R4 refactoring attempt (8 factors) was explored to test whether the RC1 social/relational engagement factor could be decomposed further. The additional factor failed to achieve eigenvalue >1.0 and produced cross-loadings that reduced interpretive clarity. R3 (7 factors) was retained as the most parsimonious solution with clean separation between constructs.

Cluster count was selected at k=4 via silhouette analysis (0.18, modest but stable). k=5 was tested and produced a micro-cluster (n=47) that fragmented The Accumulator without adding interpretive value — it separated a high-digital subgroup that was better captured as a within-cluster dimension. k=3 merged The Ethical Keeper and The Seasonal Clearer into an undifferentiated low-engagement group, losing the critical values/inertia distinction.

Gower distance with k-medoids (PAM) was tested as an alternative clustering approach that handles mixed variable types without distance assumptions. It produced a broadly similar 4-cluster solution (Adjusted Rand Index 0.61 with the PCA-based clusters) but with less clean separation on the sustainability and disposal factors. The PCA + k-means pipeline was retained on both silhouette score and interpretive grounds.