Organizational decisions are increasingly produced through infrastructures that combine managerial judgment, datafication, algorithmic recommendation, monitoring, and automated classification. This expansion complicates conventional fairness analysis because a decision may be explained yet remain difficult to challenge, formally reviewable yet practically irreversible, or corrected without repairing the trust damaged by the original process. This Original Conceptual Framework Article develops a proposed Justice-and-Repair Framework for analyzing such conditions. The framework integrates organizational justice, explainability as procedural information, contestability and employee standing, moral accountability after error, and trust repair and remediation. It proposes that legitimate repair requires more than favorable outcomes or explanatory disclosure: affected employees must have meaningful routes to consequential review, responsible organizational actors must remain identifiable after technological delegation, and remedies must be capable of addressing relational, substantive, and structural dimensions of harm. The article further proposes that decision-system evaluation should distinguish formal voice from substantive influence, technological capability from legitimate authority, and restored confidence from demonstrated correction of injustice. These relationships are conceptual rather than empirically validated and are expected to vary with decision stakes, reversibility, hierarchy, workload, prior trust, and violation characteristics. The framework therefore functions as a theory-building architecture and testable research agenda, not as a universal prescription or deployment standard. Its principal contribution is to connect justice at the decision stage with accountability and repair after error.
