Self-retraction as redemption: Forgiveness for repentant authors.

Area of Science:

• Bibliometrics
• Scientific publishing
• Research integrity

Background:

• Traditional responses to publication misconduct involve penalties, potentially hindering retractions.
• Systemic obstacles and collusion can impede the retraction of fraudulent publications.
• Encouraging self-retraction by waiving punishments is an underexplored strategy to refine scientific discourse.

Purpose of the Study:

• To propose a novel model, Hierarchical Self-Retraction Forgiveness (HSRF), to facilitate self-retraction of publications involving misconduct.
• To mitigate systemic barriers that prevent authors and institutions from retracting fraudulent research.
• To foster a more transparent and accurate scientific record by reducing fear of penalties.

Main Methods:

• Development of the Hierarchical Self-Retraction Forgiveness (HSRF) model.
• Integration of safeguards to prevent exploitation of the forgiveness policy.
• Conceptual framework addressing authors, institutions, and higher supporting systems.

Main Results:

• The HSRF model provides a framework for leniency in cases of self-reported misconduct.
• Alleviating reputational and institutional concerns can incentivize self-retraction.
• Safeguards are incorporated to ensure the model's responsible application.

Conclusions:

• The HSRF model offers a potential solution to accelerate the refinement of scientific discourse.
• Encouraging self-retraction through forgiveness can enhance research integrity and reduce fraudulent publications.
• Continuous dialogue and refinement are recommended for optimal effectiveness of the HSRF model.