Bibliographic record
Abstract
Unconscionability can and should be used in appropriate cases to ensure access to justice for contracting parties in Canada. In this comment, I articulate a test for the application of unconscionability to what I call access clauses — clauses such as arbitration clauses and forum selection clauses that affect how a contracting party can access an adjudicative process. This test follows, and rationalises, recent judicial attempts to apply unconscionability to access clauses in the cases of Douez v Facebook and Heller v Uber. Previous attempts to make sense of — or criticise — these applications of unconscionability, have been limited in attempting to discipline the doctrine to the logic of contract law. But unconscionability is equitable: it relieves parties from contractual obligations despite every requirement of contract law being met. Cases applying unconscionability to ensure access to justice, which access clauses sometimes deny, reflect a new kind of inequity from which courts will relieve, rather than a new error of contractual logic. That inequity is an inaccess to justice.
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 | 0.017 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.029 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 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".