Bibliographic record
Abstract
Contracts: Cases and Commentaries, Tenth Edition continues to be the teaching tool of choice among Canadian contracts professors. This book allows students to learn the law of contracts by first gaining a familiarity with the substantive law. Substantive law includes the law relating to the formation of contracts, factors affecting the validity of contracts, and remedies for when a party breaches the contract. A familiarity with these principles will serve as a useful stepping stone to courses drawing on the general principles of contract law,— such as the sale of goods, consumer protection, insurance, real estate transactions, and labour law. This book will teach students how to engage in analyzing areas of law where overlapping or conflicting values are at stake, such as human rights law and property law, by reflecting on a value fundamental to the law of contracts, such as freedom of contract. Furthermore, this book will facilitate the acquisition of a variety of basic skills associated with the analysis and use of case law and, to a lesser extent, legislation. It is designed as an aid to the acquisition of these essential skills, via the study and discussion of the decisions of the courts, as well as statutory law and academic comment.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.065 | 0.025 |
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".