Substantial research documents produced through sustained human-AI collaboration. Evidence reviews, conceptual frameworks, and analytical reports that demonstrate what structured AI-assisted research looks like in practice.
All documents in this collection were produced through structured human-AI collaboration using Claude (Anthropic). Sources are verified against peer-reviewed databases. No references have been fabricated. Each report carries its own anti-hallucination statement and methodology declaration.
A comprehensive synthesis of peer-reviewed evidence (2020–2026) on coaching and coaching-adjacent psychosocial interventions for adults with ADHD. Covers workplace outcomes, methodological debates, and the terminological landscape of the field.
A critical literature review examining the ideological assumptions embedded in AI system design — drawing on political economy, critical theory, STS, and Foucauldian analysis. Argues that dominant AI paradigms reflect neoliberal logics of optimisation and competition.
Conceptual FrameworkA reference framework for understanding context engineering in AI systems. Defines the four disciplines of AI prompting — prompt craft, context engineering, intent engineering, and agent orchestration — and their practical implications for human-AI collaboration.
Terminology GuideA plain-language guide to the evolving vocabulary of discrimination against neurodivergent people — covering neuronormativity, ableism, sanism, masking, and the contested debates around language in academic, legal, and community contexts.
Research MethodologyThe methodological framework for a large-scale AI-assisted discourse analysis of 20,000 Reddit posts about ADHD. Documents the AIDA method (AI-Assisted Inductive Discourse Analysis), sampling strategy, analytical pipeline, and epistemological positioning.