Contract Law’s Red Herring: Exposing “Intention” as a Guise for Consideration
Bibliographic record
Abstract
This paper describes and evaluates the contested fourth requirement for contract formation: the intention of both parties that their agreement be legally enforceable (“legal intention”). I begin with an overview of the jurisprudence on legal intention, ending with the Supreme Court of Canada’s most recent pronouncement in Ethiopian Orthodox Church of Canada St. Mary Cathedral v Aga. While the Court in this case affirmed that legal intention is to be treated as a fourth requirement, its analysis reveals precisely the reason why it should not be: when courts purport to analyze legal intention, an inherently difficult value to assess, they often lapse into a veiled assessment of consideration instead. I draw on Peter Benson's conception of "robust consideration" to argue that we should dispense with the legal intention requirement. In its place, a clear test for robust consideration would allow courts to conduct self-aware analyses free from contorted intention assessments. I conclude by offering an interpretation of Balfour v Balfour, the seminar case supporting a legal intention requirement, that is consistent with my proposed approach to contract formation.
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.059 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".