Beyond Trait Scores: A Framework for contextual, role-specific behavioral Assessment in High-Stakes People Decisions

High-stakes people decisions now extend beyond hiring to promotion, redeployment, retention, and workforce restructuring, often under time pressure and growing governance scrutiny. Traditional psychometric instruments have made important contributions by standardising evidence about individual differences, but they were not primarily designed to produce role-specific, evidence-cited behavioural reasoning for live organisational decisions. This paper proposes the Contextual Behavioural Assessment Framework (CBAF), a conceptual and methodological framework that shifts the unit of analysis from trait description to situational behavioural inference. The framework integrates four design principles: career-stage calibration, role and environment contextualisation, scenario-based behavioural elicitation grounded in situational judgement test methodology, and cross-dimensional AI-supported inference. The paper reviews literature on personnel selection, situational judgement testing, trait psychometrics, AI in HR, algorithmic fairness, explainability, and auditability. It also distinguishes practice-informed conceptual development from formal empirical validation. The CBAF is presented as a responsible assessment architecture for making behavioural reasoning more relevant, transparent, consistent, and auditable while preserving human authority at the decision layer.