Library

This library is the knowledge base underlying ContextWell Lab’s research and problem framing.

It brings together core publications and reference materials that inform how we approach human capacity, well-being, and oversight in intelligent systems.

Featured

Well-Being as Embedded Infrastructure in the Intelligence Era
White paper · 2026 · DOI: 10.5281/zenodo.18121093
A structural framing of well-being and human oversight as infrastructure for governable intelligent systems.

Publications

Towards an inclusive digital health ecosystem
Bulletin of the World Health Organization · 2024

Positions digital inclusion as a structural requirement for equitable digital health systems.

Barriers and Facilitators of International Health Care Students’ Well-Being in Higher Education: Protocol for a Systematic Integrative Review
JMIR Research Protocols · 2024

Protocol outlining methods for examining contextual factors shaping international health care students’ well-being.

Artificial intelligence for contextual well-being: Protocol for an exploratory sequential mixed methods study with medical students as a social microcosm
PLOS ONE · 2025

Introduces an exploratory sequential mixed-methods design to operationalise contextual well-being with AI in medical education.

General practice professionals’ perspectives on cardiovascular risk assessment in patients diagnosed with mental health disorders: an embedded mixed-methods study
Irish Journal of Psychological Medicine · 2025

Explores how cardiovascular risk assessment is approached in general practice for patients with mental health disorders.

Beyond Procedural Compliance: Human Oversight as a Dimension of Well-being Efficacy in AI Governance
arXiv · 2025 · arXiv:2512.13768

Reframes human oversight as a trainable capacity linking regulatory intent with human capability development.

AI Contextual Framework: A Zoning Approach to Ethical AI Deployment
AAAI/ACM Conference on AI, Ethics, and Society (AIES) · 2025

Proposes a zoning-based framework for context-sensitive ethical AI deployment.