This working paper highlights a judgment failure in AI recommendations for journal submissions, indicating significant implications for manuscript acceptance.
AI systems are increasingly used as decision aids in scholarly workflows, including venue selection and “journal fit” advice. Yet journal fit is not merely a topical or formatting judgement; it is an institutional judgement about admissible contribution types (genre), theoretical anchoring expectations, and editorial culture. This working paper reports a de-identified, trace-based single-episode case in which multiple AI systems converged on a high-probability journal recommendation for a culture/heritage-adjacent AI manuscript, citing topical relevance and article-like surface structure. The subsequent editorial outcome (reported here as a paraphrased summary, not a quotation) rejected the manuscript as failing the venue’s expectations for an admissible journal article genre.
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Sincere Ann Ma (2026) studied this question.
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