Proving the Matrix: On the Admissibility and Use of Prior Negotiation Evidence as an Aid to Contractual Interpretation
Bibliographic record
Abstract
This article examines the relevance and admissibility of prior negotiation evidence in contract interpretation. According to a long-established common law rule (“exclusionary rule”), the evidence of pre-contract negotiations is not admissible as an aid to contract interpretation. This study argues that the exclusionary rule is unjustified and should be abandoned. Judges should be allowed to use prior negotiation evidence to support inferences about the existence of the empirical facts constituting the relevant factual matrix, while the use of such evidence should not be allowed to support interpretive inferences about the meaning of the contract language. The distinction between empirical and interpretive inferences helps identify and explain the situations in which prior negotiation evidence assists the process of contractual interpretation.
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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 | 0.152 | 0.476 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.008 | 0.054 |
| Scholarly communication | 0.016 | 0.058 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 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".