Social Science Research 6.0: A Proof-of-Integrity Framework for Tamper-Evident Survey Instruments Using an Open-Source R Package

Survey-based social science research increasingly depends on digital questionnaires, browserbased data collection, automated statistical workflows, and reproducible reports. Yet the integrity of the research objects that connect these stages remains weak in many projects. Questionnaire files, response datasets, analysis scripts, and reports are often stored as separate artefacts, and when any one of them is changed after fieldwork or after submission, reviewers and institutions may lack a simple way to verify whether the file is identical to the version used earlier. This paper proposes Social Science Research 6.0 as a proof-of-integrity framework for tamper-evident survey workflows. The framework uses SHA-256 hashing to assign verifiable digests to survey instruments, response datasets, analysis plans, scripts, and report outputs, and records them in a structured manifest that can be verified at any later point. The approach is demonstrated using surveyframe, an open-source R package that represents a questionnaire as a typed survey object, saves it as a hashed .sframe file, validates item and scale structure, reads response data, checks quality, scores scales, prepares analysis plans, and generates reproducible reports. A synthetic proof-of-concept confirms that the framework detects instrument modification, response tampering, and analysis-plan drift in all tested scenarios. The contribution is a low-cost, software-only method for improving trust, transparency, and auditability in digital social science research without requiring blockchain infrastructure or proprietary survey platforms.