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Research ethics and attribution
Honest research practice: attribution and citation, priority and authorship, plagiarism, disclosure of computational and AI assistance, handling errors, and clearly separating established results from conjecture.
math.found.research-ethics
Se basa en
Requisitos previos obligatorios, hasta el fondo: 12
Aprenderás a
- Cite sources accurately, including results learned from talks, software, databases and AI systems.
- Decide authorship and acknowledgements fairly in a collaborative project, knowing that mathematics commonly lists authors alphabetically.
- Respond appropriately when an error is found in one's own published work or in someone else's.
Definición
- Plagiarism is presenting another person's words, ideas or results as one's own.
- Attribution credits the origin of an idea, result, proof, code or data set.
- An erratum or corrigendum is a published correction.
Teorema
- Mathematical truth does not depend on who discovers it, but credit for a discovery belongs to those who made it.
- Agreement among several AI systems is not a substitute for verification: their errors may be correlated in unknown ways, so proofs must be checked by people or by verified formal methods.
Errores frecuentes
- Thinking well-known results need no citation.
- Treating AI-generated text or proofs as exempt from attribution and verification.
- Believing that admitting an error does more harm than concealing it.