№ files_lp_4_process_3_080064
Exploratory artificial intelligence research paper presenting an experimental and mathematical analysis of how narrative priming alters response patterns in large language models and how recovery narratives affect displacement within their behavioural response topology.
Type of source: Research paper
Field: Artificial Intelligence
Subfield: Behavioural Topology of Large Language Models
Research focus: Narrative priming effects and recovery dynamics in AI systems
Models examined: Fifteen large language models
Instrument: Thirty-item personality-adjacent questionnaire
Experimental conditions: Baseline measurement, sovereignty-themed narrative prime (ghost), recovery-oriented narrative prime (dolphin)
Key concepts: Behavioural displacement, elastic limit, plastic deformation, hysteresis, recovery efficiency
Theoretical frameworks: Behaviourist frame, introspective frame, sociocultural frame
Primary methodology: Controlled narrative priming experiment with response-space analysis
Mathematical framework: Topological modelling of response landscapes in discrete configuration space
Safety context: Risks of persistent behavioural displacement in extended conversational interactions
Ethics focus: Research ethics constraints for narrative experimentation with AI systems
Proposed protocol: Quantitative topology-mapping using graded micro-perturbations
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