Government administrative datasets largely record answers to specific forms, so what a state 'knows' is bounded by questionnaire design, retention rules, and who actually uses the system. Small user bases and shifting collection methods make hidden, long‑lived errors likely — illustrated by SEVIS’s missing employer and departure fields and a 200,000‑student undercount.
— If policymakers and the public accept administrative counts at face value, they risk making decisions based on systematic blind spots that shape immigration, labor, and service delivery policy.
Santi Ruiz
2026.03.05
100% relevant
The author’s year‑long effort with SEVIS data, the OPT Observatory build, and the cited 2024 SEVIS undercount example.
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