The Three Axes of Success: A Three-Dimensional Framework for Career Decision-Making

• URL: http://arxiv.org/abs/2601.17023v1
• Date: Fri, 16 Jan 2026 16:54:56 GMT
• Title: The Three Axes of Success: A Three-Dimensional Framework for Career Decision-Making
• Authors: Meng-Chi Chen,
• Abstract summary: We propose The Three Axes of Success, a normative decision framework decomposing career trajectories into Wealth, Autonomy, and Meaning.<n>We operationalize each axis through measurable proxies, analyze career archetypes, and derive sequential or simultaneous optimization strategies under uncertainty.<n>This provides the first unified decision-theoretic treatment of career success, integrating insights from human capital theory, self-determination theory, and effective altruism into a coherent architecture for rational career design.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Career decision-making is a socio-technical problem: individuals exercise bounded agency while navigating labor market institutions, organizational incentive structures, and information asymmetries that shape feasible trajectories. Existing frameworks optimize along single dimensions - financial returns, work-life balance, or mission alignment - without explicit models for inter-dimensional tradeoffs or temporal dynamics. We propose The Three Axes of Success, a normative decision framework decomposing career trajectories into Wealth (career capital accumulation and economic optionality), Autonomy (control over task selection, temporal allocation, and strategic direction), and Meaning (counterfactual social impact scaled by problem importance and personal replaceability). We formalize coupling dynamics between axes: the adjacent possible mechanism by which skill frontiers enable mission discovery, creating nonlinear Wealth -> Meaning transitions; autonomy prerequisites where insufficient career capital triggers control traps; and dual-career household constraints that yield Pareto-suboptimal Nash equilibria under independent optimization. We operationalize each axis through measurable proxies, analyze prototypical career archetypes - industrial R&D, academia, entrepreneurship - as points in (W, A, M)-space, and derive sequential versus simultaneous optimization strategies under uncertainty. The framework converts implicit career anxiety into explicit multi-objective optimization problems with satisficing thresholds, structuring the human-system interaction between individual deliberation and institutional constraints. This provides the first unified decision-theoretic treatment of career success, integrating insights from human capital theory, self-determination theory, and effective altruism into a coherent architecture for rational career design.

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