Legal Relationship between Universities and their Students – How Accountable and to what Extent in Law are Universities Liable for Student Suicides?
Bibliographic record
Abstract
This article addresses how the relationship in law of universities and their students is to be characterised. Its main purpose is to establish where legal liability lies in the case of a student committing suicide, whilst undergoing an educational qualification. Characterisation of the relationship between universities and their students has been included within a number of models which are set out and assessed, the aim being to show the range of characterisation and at the same time point out the defect(s) in each characterisation. This analysis is undertaken in searching for a more meaningful and coherent model of the legal relationship between the university and the student. A legal framework of accountability is essential. Exploration of more conventional ways of addressing this, and alternatives, is required. The article therefore includes for consideration a less fashionable potential classification of a fiduciary relationship between universities and their students. It explores, too, the possibility in public law of founding a breach of a substantive legitimate expectation challenge where promises of safeguarding have been made to the now deceased student. This phenomenon goes beyond the United Kingdom, so reference is made to case law in other jurisdictions, such as Canada and USA.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.007 |
| 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".