MERIT supports the quality- and impact-oriented assessment of research and researchers, to increase the robustness and fairness of decision-making. 

The portal follows these principles:

• Quality over quantity: multi-dimensional, criteria-based assessment, using a hybrid application format that includes narrative as well as list elements. Journal Impact Factor and h-index are neither requested nor generated.
• Explicit criteria: assessment is based on defined, structured criteria. Implicit notions of quality or excellence are avoided.
• Transparent, structured criteria: application form and assessment is aligned with key phases of research and careers.
• Diversity of criteria: accounting for varied research outputs and career paths.
• Structured assessment aids: based on the application form. No additional, hidden criteria are applied.
• Context-sensitive assessment: criteria are selected and weighed according to the call, research area, career stage, academic age and DEI aspects. Not all criteria apply equally to all calls.
• Qualitative ratings (e.g. strong – medium – weak) rather than numerical scores, to avoid a false sense of accuracy. No ranking or cut-offs from vague scores.
• Reflexive, content-oriented peer review: supported by structured procedures, training materials and bias-reduction strategies (e.g. anonymization, academic age) for reviewers.
• Open feedback to applicants (open peer review): to improve assessment quality and accountability on the reviewers side and support knowledge exchange.
• Transparent AI use: applicants and reviewer disclose use of generative AI in application preparation or assessments, in line with the DFG statement on the Influence of Generative Models of Text and Image Creation on Science and the Humanities (2023).