Institutional principles
Governance Principles
These principles describe how RIFOR intends to communicate affiliation, research review, conflicts, corrections, and AI-assisted work responsibly.
Current status
This is a public principles statement, not a claim of accreditation, nonprofit status, governmental recognition, or external certification. Formal policies and named governance bodies should be published here only after adoption.
Core principles
Research integrity
Methods, evidence, citations, uncertainties, and limitations should be represented honestly.
Transparent affiliation
RIFOR affiliation should state its nature and must not imply employment, a degree, accreditation, or endorsement that does not exist.
Conflict disclosure
Reviewers, contributors, and decision-makers should disclose interests that could reasonably affect their judgment.
Responsible AI use
AI output should be treated as fallible analysis, with meaningful uncertainty and disagreement disclosed.
Corrections
Material errors in public records should be corrected promptly, with changes documented when appropriate.
Privacy and consent
Researcher profiles and personal information should be published only with a valid purpose, verification, and permission.
Questions and concerns
Questions about affiliations, public records, review practices, corrections, or potential conflicts can be sent to info@rifor.org. RIFOR should document a more specific escalation and appeals process as its operations develop.