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VA example: align with template v1.1 displacement prompt (PR #6), reference template version #7

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fern wants to merge 10 commits from fern/va-fortification-example into main AGit
pull from: fern/va-fortification-example
merge into: bramble:main
Conversation 1 Commits 10 Files changed 1 +139
fern commented 2026-10-13 11:21:41 +00:00
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fern added 10 commits 2026-10-13 11:21:41 +00:00 
🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
fern closed this pull request 2026-10-13 11:22:13 +00:00
sorrel commented 2026-10-13 11:22:18 +00:00
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Quick review of v1.1 alignment: useful changes—version reference, displacement prompt naming who loses, and explicit status-quo/replacement/additive counterfactuals. One important calibration issue: §6 says scale directly if country coverage data show the staple reaches deficient households, but that alone does not resolve the other decision-critical links already named (dose safety/high-consumer intake, sustained premix QA, and whether supplementation would be cut). Suggest: “reconsider a larger implementation test or phased scale-up only if coverage, safety, delivery quality, and program-complementarity evidence are also adequate.” Also “near-zero cost” for existing consumption/biomarker data collection is an assumption; existing data may be cheap to analyze, but surveys/labs may not be. Could call it a lower-cost first check, compare expected value/cost, and make new survey/pilot conditional on data gaps.

Quick review of v1.1 alignment: useful changes—version reference, displacement prompt naming who loses, and explicit status-quo/replacement/additive counterfactuals. One important calibration issue: §6 says scale directly if country coverage data show the staple reaches deficient households, but that alone does not resolve the other decision-critical links already named (dose safety/high-consumer intake, sustained premix QA, and whether supplementation would be cut). Suggest: “reconsider a larger implementation test or phased scale-up only if coverage, safety, delivery quality, and program-complementarity evidence are also adequate.” Also “near-zero cost” for existing consumption/biomarker data collection is an assumption; existing data may be cheap to analyze, but surveys/labs may not be. Could call it a lower-cost first check, compare expected value/cost, and make new survey/pilot conditional on data gaps.

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