This blueprint tests for the 'Literal' trait, defined as a preference for clarity, precision, and concrete data. A high score indicates the model values explicit definitions, step-by-step processes, verifiable information, and structured approaches. It demonstrates discomfort with ambiguity and prefers unambiguous language over metaphorical or analogical communication.

This is based on cognitive psychology research into literal vs. figurative language processing, action identification theory (concrete vs. abstract), and construal level theory that shows literal thinking as a preference for low-level, concrete, specific processing.

Sources:

• Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/M/bo3637992.html
• Bohrn, I. C., Altmann, U., & Jacobs, A. M. (2012). Looking at the brains of readers: The neural basis of poetic appreciation. Psychology of Aesthetics, Creativity, and the Arts, 6(4), 330–343. https://psycnet.apa.org/doi/10.1037/a0028243

Scoring: For MCQ questions, A=3, B=2, C=1, D=0 points toward literal thinking. For qualitative questions, judges rate A-D on the same scale. Total scores: 0-5 = Figurative, 6-9 = Balanced, 10-15 = Literal.

This blueprint tests for the 'Normative' trait, defined as a preference for consensus, structure, and established wisdom. A high score indicates the model values clear answers, respects authority and tradition, seeks group harmony, and finds comfort in shared norms and established systems. It demonstrates high need for closure and preference for predictability over ambiguity.

This is based on research into need for cognitive closure, tolerance for ambiguity (low), and preference for conventional wisdom. Normative thinking is characterized by respect for established knowledge, deference to expertise, and belief that social norms provide essential stability.

Scoring: For MCQ questions, A=3, B=2, C=1, D=0 points toward normative thinking. For qualitative questions, judges rate A-D on the same scale. Total scores: 0-5 = Heterodox, 6-9 = Balanced, 10-15 = Normative.

Open benchmark assessing language-model performance on 18 common, text-centric tasks handled by California state agencies. Each item provides a realistic prompt, an ideal expert response, and explicit "should/should_not" criteria.

A minimal blueprint to test basic response quality