Bibliographic record
Abstract
Good faith has its roots in Roman law and is part of European legal culture. English law allowed recourse to notions of good faith and commercial expectations, however 19th and early 20th century English law regarded the commercial need for certainty in contract law as a reason for rejecting requirements of good faith in performance. The fears most commonly expressed about the adoption of a doctrine of good faith are that it is inconsistent with the principle of freedom of contract and will create uncertainty in the law and for commercial dealings because its content is vague and subjective, and would permit ad hoc judicial moralism. The United States and Canada regard good faith as important to the law of contract; Australia, New Zealand, Hong Kong and the UK have not adopted an overarching principle of good faith in performance of contractual rights and duties, although this paper argues that aspects of good faith may be present in the doctrines and remedies provided by the common law and by equity. The question arises whether a broad doctrine of good faith is necessary. So long as the courts approach contracts by reference to reasonable expectations of the parties and the many doctrines which have been developed, and the process of construction that has been used by the courts to regulate contractual performance may fill the gap created by there being no general duty of good faith.
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 | 0.024 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.045 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".