🧠 Ethics in the Publication and Application of Research
📌 Key terms
| Term | Definition |
|---|---|
| Integrity | Honest and accurate reporting of data and results. |
| Plagiarism | Presenting another’s work or data as one’s own. |
| Fabrication/Falsification | Creating or manipulating data to fit desired outcomes. |
| Conflict of Interest | Bias in research or publication due to personal or financial gain. |
| Informed Application | Ensuring research findings are applied ethically and not misused (e.g., military or political manipulation). |
| Peer Review | Independent evaluation by experts to ensure validity and credibility. |
📌 Notes
Ethics extends beyond data collection to the publication, communication, and application of research findings.
1. Publication Ethics
- Researchers must report data truthfully and transparently.
- Fabrication and falsification undermine public trust (e.g., Diederik Stapel case).
- Plagiarism breaches academic integrity.
2. Peer Review Process
- Ensures accuracy, credibility, and quality control.
- Bias or conflict of interest (e.g., funding sources) must be disclosed.
3. Ethical Application
- Research outcomes should benefit society, not harm it.
- Example: Misuse of intelligence testing for eugenics in early 20th century.
4. Open Science Movement
- Encourages data sharing, replication, and transparency.
- Addresses the replication crisis in psychology by promoting accountability.
🔍Tok link
Can scientific knowledge remain objective when its publication and use depend on human values?
TOK Prompt: “Who owns knowledge, and who is responsible for its consequences?”
🌐 Real-World Connection
Modern journals require ethical declarations, data transparency, and conflict-of-interest statements.
Ethical misuse of research (e.g., in advertising or warfare) remains a global concern.
❤️ CAS Link
- Students can develop school codes of academic honesty or conduct workshops on plagiarism and integrity, linking service and ethical citizenship.
🧠 IA Guidance
- In your IA evaluation, mention publication ethics and transparency — report data honestly.
- Never manipulate or omit data to “improve” results.
- Reflect on how integrity ensures reliability in psychological research.
🧠 Examiner Tips
- Examiners expect clear mention of ethical responsibility in reporting and application.
- Use concrete examples (e.g., replication crisis, Diederik Stapel).
- Discuss long-term consequences of unethical publication.