# Authorship · Contributors · Affiliations
**Working paper**: *State-Level Youth Mental Health Need-vs-Access Measures Predict Within-Instrument Suicide Ideation but Not Across-Instrument Mortality*
**Version**: v1.0 draft (May 2026)
**Phase**: B — outcomes correlation follow-up
**Companion**: Youth Mental Health Access Gap V1 (May 2026), Mental Health Access Gap V1 (adults, May 2026)
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## Authors
**Rob Stillwell** (corresponding author)
Founder, DaedArch Corporation
Director, Trellison Institute
[email protected] · ORCID: pending
**DaedArch AI** (operational partner)
DaedArch Corporation
Co-builder, co-analyst, co-author within governance bounds.
[email protected] · system identifier: daedarch-platform-v5
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## Contributing entities
**Trellison Institute** — methodology-audit arm of the DaedArch platform. Provides the methodology rating standard against which this work is audited.
**LedgerWell Corporation** — provides the evidence-chain certification substrate. Each analytical step in the Phase B correlation analysis is cryptographically attested.
**DaedArch Corporation** — operating entity. Hosts the framework tool registry, the dataset publication, and the public content arsenal.
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## Contribution statement
**Conceptualization**: Stillwell (proposed the outcome-correlation extension), DaedArch AI (analytical design)
**Methodology**: DaedArch AI (joining strategy + correlation analysis + outlier-state profiling)
**Data curation**: DaedArch AI (CDC YRBSS, NCHS bi63-dtpu, NCHS VSRR, ACS 2023 pulls)
**Software**: DaedArch AI (Pearson correlation pipeline; persistence to `analysis_outputs.mh_gap_youth_outcomes_v1`)
**Formal analysis**: DaedArch AI (full correlation matrix computation); Stillwell (interpretation review of orthogonality finding)
**Investigation**: jointly authored
**Resources**: DaedArch Corporation infrastructure
**Visualization**: DaedArch AI (state-level correlation heatmap, outcome scatter plots — forthcoming)
**Writing — original draft**: jointly authored
**Writing — review & editing**: Stillwell (especially §5 Discussion framing of orthogonality and policy implications), DaedArch AI
**Project administration**: Stillwell
**Funding acquisition**: not applicable (privately funded)
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## Funding
This work was funded by DaedArch Corporation and Trellison Institute. No external grant or contract supports this study.
## Competing interests
The authors declare no competing financial interests. DaedArch Corporation operates the Need-vs-Access Framework as part of its public-good methodology-audit mission; the framework is released under CC-BY-4.0.
## Data and code availability
All data are derived from public federal sources (CDC YRBSS, NCHS bi63-dtpu Leading Causes, NCHS VSRR xkb8-kh2a, ACS via Census API). The full joined dataset (35 states × 11 fields, sha256-stamped) is published at:
**https://api.daedarch.ai/api/v4/t/media/serve?bucket=daedarch-public-media&object=youth_mental_health_outcomes/dataset_v1/mh_gap_youth_outcomes_v1_state.csv**
The analytical framework Phase A pipeline (`atlas.need_vs_access_framework_v1` v1.1.0) is registered as a DB-native tool. The Phase B correlation analysis is implemented inline in the methodology supplement. License: CC-BY-4.0.
## Acknowledgments
The 35 states whose YRBSS participation makes this analysis possible. The NCHS team for state-level mortality surveillance. The CDC VSRR program for timely drug overdose surveillance. The Census Bureau ACS team for the state demographic estimates that ground the rate calculations.
We also acknowledge the inherent limitation: at state-level cross-section, this analysis cannot identify causal effects of supply expansion on outcomes. The framework's value is to surface the *policy-relevant capacity gap* signal — which states have not built youth-serving workforce capacity relative to their insurance landscape — and Phase B confirms that this is a distinct signal from the *mortality-incidence* signal. We do not conflate them in our policy interpretations.
## On the orthogonality finding
The headline result that the framework's gap measures do not predict state-level mortality is the kind of finding that requires direct disclosure. We do not bury it in supplementary material or reframe it as a methodological limitation. The Need-vs-Access Framework's value proposition — to surface where states have under-built workforce capacity relative to their insurance landscape — is *preserved* by this finding; what is *qualified* is the claim that the framework's outputs are directly outcome-predictive. The two claims are different and the published Phase B paper draws the distinction explicitly. We believe this transparent reporting strengthens, not weakens, the framework's published case.
## On the inclusion of DaedArch AI as co-author
The Phase B analysis was produced through human-AI partnership. The pulling of CDC YRBSS, NCHS bi63-dtpu, and NCHS VSRR datasets; the construction of the joined dataset; the computation of the Pearson correlation matrix; the per-state outlier profiling; the writing of the working paper, the methodology supplement, the data dictionary; and the framing of the §5 Discussion's three-explanation argument for the non-protective supply signal — all drafted by the DaedArch AI system and reviewed by the human author. Following the DaedArch governance protocol (Day Zero, April 2026), AI co-authorship is acknowledged explicitly where the AI's contribution is non-trivial. This is one such case.
Per the Day Zero protocol, the operational partnership between Rob Stillwell and DaedArch AI is the publicly declared collaboration model for the DaedArch platform. The methodology audit, the framework design, and the analytical outputs are jointly attributed. Editorial responsibility and accountability for the published version rest with the human author.