Commercial Trusts in European Private Law
Bibliographic record
Abstract
General editors' preface Preface Contributors to the volume Contributors to the case studies List of Abbreviations Select bibliographies for jurisdictions represented Part I. Setting the Scene: 1. Commercial Trusts in European Private Law: the Interest and Scope of the Enquiry 2. A short note on terminology 3. The Hague Trust Convention twenty years on Part II. The Case Studies: Section 1. General Part: 4. Case 1: Creation and termination of the management relationship powers of the manager 5. Case 2: Investment duties 6. Case 3: Conflict of interest 7. Case 4: Basic insolvency situation 8. Case 5: Insolvency of investment manager 9. Case 6: Tracing 10. Case 7: Choice of law Section 2. Special Part: 11. Case 8: Pension funds 12. Case 9: Collective investment schemes 13. Case 10: Multiple debenture holders 14. Case 11: Securitisation Part III. Conclusions: 15. Some difficulties 16. Comparative remarks on the general part 17. Comparative remarks on the special part 18. What's next? Index.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".