ARXIV:2604.16132 · AI FOR SOCIAL SCIENCE RESEARCH · SUBMITTED 20 APR · 20:24 UTC · FRESHNESS STALE

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Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors

Jessica H. Zhu · Shayla Stringfield · Vahe Zaprosyan · Michael Wagner · Michel Cukier · Joseph B. Richardson · arXiv

Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

Ship in 2-4 weeks›Score5.0Evidence unverified

Opportunity summary

Pain Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

Evidence 0 refs | 3 sources | 50% coverage

Blocker Evidence unverified

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PROBLEM

Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges. Qualitative research, including in-depth interviews, is a valuable tool for understanding the personal and societal consequences of community…

METHOD

Full abstract

Firearm violence is a pressing public health issue, yet research into survivors' lived experiences remains underfunded and difficult to scale. Qualitative research, including in-depth interviews, is a valuable tool for understanding the personal and societal consequences of community firearm violence and designing effective interventions. However, manually analyzing these narratives through thematic analysis and inductive coding is time-consuming and labor-intensive. Recent advancements in large language models (LLMs) have opened the door to automating this process, though concerns remain about whether these models can accurately and ethically capture the experiences of vulnerable populations. In this study, we assess the use of open-source LLMs to inductively code interviews with 21 Black men who have survived community firearm violence. Our results demonstrate that while some configurations of LLMs can identify important codes, overall relevance remains low and is highly sensitive to data processing. Furthermore, LLM guardrails lead to substantial narrative erasure. These findings highlight both the potential and limitations of LLM-assisted qualitative coding and underscore the ethical challenges of applying AI in research involving marginalized communities.

RESULT

ScienceToStartup currently rates this 5.0/10 on the public viability pass. Our results demonstrate that while some configurations of LLMs can identify important codes, overall relevance remains low and is highly sensitive to data processing.…

WHY NOW

AI for Social Science Research moved forward this cycle; last verified April 2026. Public score 5.0/10. Production flags indicate code availability.

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Opportunity summary

Score5.0

PainLeveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

Evidence0 refs | 3 sources | 50% coverage

Blockerno shell-level blocker reported

Analysis summary

Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

VerifiedSource: PDF linkedVerifiedPaperPack: citation fields availablePartialProof: unverified proof status

Competitive landscape

Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

Segment

AI for Social Science Research

Adoption evidence

No public code link in the paper record yet

Commercial read

5.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

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Competitive landscape

Leveraging open-source LLMs to code qualitative interviews with firearm violence survivors, highlighting potential and ethical challenges.

Segment

AI for Social Science Research

Adoption evidence

No public code link in the paper record yet

Commercial read

5.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors

Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors

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