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Perspectives · an exploratory analysis
Each pair below puts two write-ups side by side. One draws on an institution working inside the system it describes. The other draws on an institution outside it. In 2 of the 18 pairs the two describe the same specific problem. In the rest they describe the same class of problem, or problems that share a field or a kind of failure. The analysis was done in February 2026, when the collection held 500 problems. It shows where the two views differ in these pairs. It does not show that they always do.
One pair as an example: water contamination treatment. Both write-ups are about the same problem.
Inside: CSIR-NEERI / CSIR-IICT (India)
Binding constraint: Systemic lab-to-field failure across all technologies over 60 years
Root cause: Technologies designed treating field conditions as edge cases
Outside: UC Berkeley / LBNL
Binding constraint: Chemistry-to-field gap for a specific technology
Root cause: Operational complexity in zero-infrastructure settings
18 pairs
Outside source
WHOException
The inside institution (ICMR) is a technical research body, and it frames the problem more narrowly than the outside source (WHO). The kind of institution affects the difference.
7-Dimension Comparison
Outside
Delivery system: antivenom requires hospitals victims cannot reach
Inside
Product mismatch: antivenom made from wrong regional venoms
Outside
Treatment architecture designed for hospitals, not communities
Inside
Regulatory standards that do not require geographic venom representativeness
Outside
Community (victims, healers, CHWs)
Inside
Regulators (CDSCO) and manufacturers
Outside
Active: cultural frameworks, care-seeking decisions, first-response capacity
Inside
Passive: patients who receive (or fail to receive) correct product
Outside
Visible: traditional healers, community health structures
Inside
Invisible: no mention of community capacity
Outside
New product architecture + community co-designed interventions
Inside
Regulatory mandate for representative venom panels + national venom biobank
Outside
Structural driver: market collapse, poverty spiral
Inside
Context: geographic inequity mentioned but not analyzed as causal
Which differences appear in this pair