Sudhanshu Rai

Independent Researcher

I build public-interest data infrastructure and work on applied econometrics and forecasting. Most of what I do starts from the same problem: a question people argue about using numbers nobody can check.

So the data, the extraction code, and the verification steps are published alongside every result — traced back to the source documents they came from.

Research

Competency Restoration Observatory

Live · Creator and maintainer

A free, public dashboard and dataset tracking how five U.S. states — Washington, Oregon, Colorado, Texas and California — meet their legal deadlines for psychiatric competency evaluation and restoration. Every figure is rebuilt from public court-monitor reports and budget documents, with each number traceable to the source page it came from. The full extraction pipeline and data are openly licensed and versioned.

The companion paper below analyses Washington's own trajectory over eight years, from years of missed deadlines to sustained compliance.

competencyrestoration.org Paper Code Data archive (DOI)

Measurement validity of AI occupational-exposure scores

Preprint · Under revision

Widely used indices claim to measure how exposed an occupation is to AI. I tested whether they measure AI specifically, or general cognitive content. Two of the three most-cited measures largely capture the latter; a third does not behave the same way. The distinction matters, because these scores are increasingly used as inputs to labour-market research.

Preprint (SocArXiv)

Model-selection instability in real-time forecasting

In preparation · Companion tool published

When several forecasting models are statistically indistinguishable, which one you pick is partly arbitrary — and that arbitrariness can propagate into decisions. This work uses unemployment-insurance claims data and the Model Confidence Set to trace how unstable model selection can flip statutory Extended Benefits trigger determinations. The diagnostic tool is already released as an open-source package.

pip install selection-fragility Code Archive (DOI)

Early warning for rural hospital closures

In development

Work in progress on predicting financial distress and closure risk among U.S. rural hospitals from public CMS filings. Not yet published.

Publications

Competency Restoration Timeliness in Washington Under Trueblood, 2018–2026. A federal court found Washington's competency-restoration system unconstitutional in 2015, for making defendants wait months in jail for a psychiatric bed. It did not turn around until years of escalating enforcement had culminated in a contempt finding and a $100 million fine. Using an open monthly panel of court-monitor data (1,033 rows, January 2018 to May 2026), I analyse inpatient restoration timeliness as an interrupted time series against the 7-day admission standard. The system was non-compliant for six years — annual median waits of 28.0 to 63.5 days, compliance rarely above 30 percent, bottoming at 6 percent in March 2023 when the median wait peaked at 97 days — then improved sharply, to a median of 5.0 days and 90.4 percent average compliance, holding across 26 months. The gain concentrated in bed-dependent services while a bed-independent comparator barely moved, and demand rose rather than fell. The improvement coincided with sustained enforcement; a single-jurisdiction design supports association, not causation. SocArXiv SSRN
Do AI Occupational-Exposure Scores Measure AI? AIOE and Eloundou (2024) largely capture cognitive content; Webb (2020) does not. SocArXiv Under revision at MPRA

Elsewhere

Happy to hear from anyone working on related questions — particularly people inside the systems this data describes.

me@sudhanshurai.org Google Scholar ORCID GitHub