Bibliographic record
Abstract
1. Introduction: Whose Ethics, Which Research?: Mike McNamee. 2. The Principle of Assumed Consent: the Ethics of Gatekeeping: Roger Homan. 3. Opening Windows, Closing Doors: Ethical Dilemmas in Educational Action Research: Les Tickle. 4. Representation, Identification and Trust: Towards an Ethics of Educational Research: Shirley Pendlebury and Penny Enslin. 5. The Ethics of Outsider Research: David Bridges. 6. Codes are Not Enough: What Philosophy can Contribute to the Ethics of Educational Research: Robin Small. 7. The Virtues and Vices of an Educational Researcher: Richard Pring. 8. The Guilt of Whistle--blowing: Conflicts in Action Research and Eduactional Ethnography: Mike McNamee. 9. Accountability and Relevance in Educational Research: Christopher Winch. 10. Educational Philosophy, Theory and Research: A Psychiatric Autobiography: David Carr. 11. Qualitative Versus Quantitative Research Design: A Plea for Paradigmatic Tolerance in Educational Research: Paul Smeyers. 12. Data Return: The Sense of the Given in Educational Research: Paul Standish. Appendix A: British Sociological Association: Statement of Ethical Practice. Appendix B: British Psychological Society Code of Conduct: A code of Conduct for Psychologists. Appendix c: British Educational Research Association: Ethical Guidelines. Appendix D: Social Sciences and Humanities Research Council of Canada: Tri--Council Policy Statement: Ethical Conduct for Research Involving Humans
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.103 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.051 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.015 | 0.021 |
| Insufficient payload (model declined to judge) | 0.014 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".