# TaMPERing with Large Language Models: A Field Guide for using Generative AI in Public Administration Research

arXiv: https://arxiv.org/abs/2504.01037 · HTML: https://mlsanity.com/paper/2504.01037/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2025.

## Built on by (most cited first, 1 of 1)

- [A Benchmark for LLM's Understanding of Middle School and High School Science Topics](https://mlsanity.com/paper/2609.32020/) (2026)

## Abstract (arXiv)

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.