2. What Counts as Misconduct?
Plagiarism: Using others’ work without citation.
Self-plagiarism: Reusing your own published material without disclosure.
Data fabrication/falsification: Inventing or manipulating data.
Improper authorship: Unfair inclusion/exclusion of authors.
Idea theft: Using confidential or unpublished work without permission.

3. Real Cases (Why This Matters)
Scientific misconduct has led to:
• Multiple paper retractions
• Loss of academic positions
• Long-term reputational damage
• Institutional investigations
Important: Many high-profile cases were uncovered years later — misconduct is often eventually
detected.

4. Historical Ethical Dilemmas
Newton vs Hooke: Hooke proposed the inverse-square idea; Newton built the full theory but gave
limited credit.
® Is developing a theory enough to override acknowledgment of prior ideas?

5. Contributor Roles (CRediT Taxonomy)
Widely adopted CRediT taxonomy promotes transparent attribution of contributions.
Examples: Conceptualization, Methodology, Data curation, Writing, Supervision.
Authorship should reflect real contributions, not hierarchy or courtesy.

6. A Simple Rule
Great science does not eliminate ethical responsibility.
If you hesitate to disclose something — it probably should be disclosed.

7. Before You Submit, Ask Yourself
Did I cite all sources?
Is my data real and reproducible?
Are contributors properly credited?
Would I be comfortable with full public scrutiny?

This material itself reflects the principles it promotes: it was developed in close interaction with
ChatGPT (OpenAI), with full transparency about its use as a supporting tool.

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Research Integrity: Not Just a Rule — A Survival Condition of Science

Research Integrity: Not Just a Rule — A Survival
Condition of Science