PREPRINT
TaMPERING with Large Language Models: A Field Guide for Generative AI in Public Administration Research Item Info
- Title:
- TaMPERING with Large Language Models: A Field Guide for Generative AI in Public Administration Research
- Authors:
- Overton, Michael Robison, Barrie Sheneman, Luke
- Year:
- 2025
- Output Type:
- Preprint
- Venue:
- arXiv
- Venue Type:
- Preprint
- Status:
- Under review
- Theme:
- Data Science and AI
- Sub-theme:
- AI
- Abstract:
- The integration of Large Language Models (LLMs) into social science research presents transformative opportunities for advancing scientific inquiry, particularly in public administration (PA). However, the absence of standardized methodologies for using LLMs poses significant challenges for ensuring transparency, reproducibility, and replicability. This manuscript introduces the TaMPER framework-a structured methodology organized around five critical decision points: Task, Model, Prompt, Evaluation, and Reporting. The TaMPER framework provides scholars with a systematic approach to leveraging LLMs effectively while addressing key challenges such as model variability, prompt design, evaluation protocols, and transparent reporting practices.
- Topics:
- Generative AI LLMs Research methods Reporting standards
- DOI:
- https://doi.org/10.48550/arXiv.2504.01037
- arXiv ID:
- 2504.01037
- Open Access Copy:
- https://doi.org/10.48550/arxiv.2504.01037
- OpenAlex ID:
- W6929243912
- Full Citation:
- Overton, Michael, Barrie Robison, and Luke Sheneman. "TaMPERING with Large Language Models: A Field Guide for Generative AI in Public Administration Research." arXiv preprint arXiv:2504.01037. https://doi.org/10.48550/arXiv.2504.01037 (Under Review)
Cite this work
Under review
Reference
Overton, Michael; Robison, Barrie; Sheneman, Luke (2025). TaMPERING with Large Language Models: A Field Guide for Generative AI in Public Administration Research. arXiv. [Under review].
View DOI record arXiv preprint
@misc{overton2025_tampering_with_large_lan,
title = {TaMPERING with Large Language Models: A Field Guide for Generative AI in Public Administration Research},
author = { Overton, Michael and Robison, Barrie and Sheneman, Luke },
year = {2025},
howpublished = {arXiv},
doi = {10.48550/arXiv.2504.01037},
eprint = {2504.01037},
archivePrefix = {arXiv},
url = {https://www.michaeloverton.net/research/items/tampering_with_large_language_models_a_field_guide_for_gener.html}
}