ClusterOS Diagnostic Profile
West Yorkshire Health Life Sciences
West Yorkshire Health Life Sciences draws £955m of UKRI lead-led funding across 1,454 grants, anchored by Leeds (51%), Leeds Teaching Hospitals Nhs Trust (14%).
The cluster shows high-confidence "Re-proving instead of narrowing" and "Forgiving instead of redesigning" behaviour — research narrative is reinforced by recurring programme launches rather than narrowing toward commercial scaling, with academic capacity reabsorbing the cluster's signal.
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Same data examined through five diagnostic lenses — Pipeline, Leverage, Triple Helix, Throughput, Collaboration. The interactive diagnostic is currently in private preview.
Sources: UKRI Gateway to Research (grants, outcomes); OpenAlex (publications); Companies House (spin-out lifecycle); DSIT (cluster mapping); Public investment data. Snapshot May 2026.
Stabilisation stacks · Why single interventions fail
Value extraction events generate narrative about ecosystem success; narrative legitimises continued extraction by framing it as ecosystem contribution; uncertainty about whether extraction is harmful absorbed by the success narrative.
"If UKRI spin-off reporting (P023) were required to separate extraction metrics (e.g., % of spin-off equity held externally, % of spin-off employment located outside West Yorkshire) from success metrics (e.g., number of spin-offs created), it might reduce the system's ability to absorb uncertainty signals without adaptation by making the difference between ecosystem contribution and value extraction visible."
Leverage hypotheses are testable perturbations, not prescriptions. Where demand-side behaviour is weakly visible, the correct move is observation — improving visibility before attempting change.
Structural resemblances · Clusters with similar stall configurations
A full ClusterOS diagnostic adds actor questionnaire data, working sessions, and anchor interviews — producing higher-confidence stall identification, board-ready stack analysis, and leverage hypotheses calibrated to your specific context.