Bibliographic record
Abstract
This article argues that there is nothing overly confusing about the law ofcausation in negligence. It attempts to define the current state of causation in Canadian negligence law with a simple goal in mind: to have a clearer more productive conversation about the law with the fundamental concepts clearly on the table. The author argues that while the leading decisions on causation are often couched in broad-based, universal terminology to refrain from inhibiting conceptual portability,the cases can be read as a sustained continuum of conversations about causation. A cohesive framework for the law is offered by taking a longitudinal perspective and focusing on the simple themes of Canadian tort law present in the causation jurisprudence: the doctrinal tests for causation, evidence for proving causation, thin skulls, and crumbing skulls. Avoiding a case-by-case dissection approach, this article instead attempts to synthesize the relevant jurisprudence. At the centre of the analysis is the bedrock principle that the negligence system is a fault-based system which relies on proving a connection between a defendant's wrongful behaviour and a plaintiff's injury.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".