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This paper presents a hybrid model combining DistilBERT embeddings with Holographic Reduced Representation vectors encoding cognitive-linguistic features (first-person pronouns, absolutist words, negative emotion ratios) to detect depression in Reddit posts, achieving a macro F1 of 0.94 and demonstrating that theory-driven features complement contextual embeddings for explainable mental health NLP.