Emojis as Expressions of Will in Contract Law: Legal Challenges and Judicial Perspectives
Bibliographic record
Abstract
Objectives: This paper examines the role of emojis in contract formation as an expression of intent within the Jordanian legal system and other comparative legal frameworks. It seeks to determine whether emojis can be taken seriously as a means of expressing an offer, acceptance, or rejection and to identify the legal challenges affecting their enforceability. Theoretical Framework: The study is based on contract law principles, particularly the requirement of clear intent in contract formation. It explores how these principles apply to digital communication and whether existing legal frameworks, such as Jordan’s Electronic Transactions Law and Civil Code, recognize emoji-based agreements. Method: A qualitative doctrinal legal analysis is used, focusing on statutory laws, case law, and academic literature. A comparative methodology is applied by reviewing judicial decisions from Canada, the US, and the EU. Results and Discussion: Findings indicate that emojis can be legally binding in some contexts, but their interpretation depends on situational factors, cultural variations, and the lack of uniformity across digital platforms. The absence of specific regulations in Jordan leaves emoji-based contract enforceability to judicial discretion. Research Implications: The study highlights the need for legislative reforms to clarify when emojis constitute binding contract expressions. It also explores how artificial intelligence and blockchain could enhance contract reliability. Originality/Value: This research contributes to digital contract discourse by proposing legal and technological solutions to improve the enforceability of emoji-based agreements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".