Find Precedents

Multi-factor similarity search using provision overlap, semantic similarity, and outcome alignment.

Select Source Case
Source Case: Duty to Report Misconduct

Case Number: 22-4

Year: 2022

Found 10 Precedents

Ranked by weighted similarity score
Matching Methods:
Cosine Semantic embedding similarity Jaccard Set intersection / union Categorical Exact match scoring
Similarity Components
Facts Similarity Cosine
60%
Discussion Similarity Cosine
64%
Provision Overlap Jaccard
10%
Outcome Match Categorical
100%
Subject Tags Jaccard
20%
Principle Tensions Jaccard
0%
What They Share

Provisions: II.5.a

Topics: Advertising Misrepresentation/Omission of Facts

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
50%
Discussion Similarity Cosine
56%
Provision Overlap Jaccard
18%
Outcome Match Categorical
100%
Subject Tags Jaccard
30%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.7 III.8.a

Topics: Public Statements and Criticism Licensure Laws Unethical Practice by Others

Outcome: Both Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
53%
Discussion Similarity Cosine
63%
Provision Overlap Jaccard
9%
Outcome Match Categorical
100%
Subject Tags Jaccard
30%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.8.a

Topics: Public Statements and Criticism Licensure Laws Advertising

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
50%
Discussion Similarity Cosine
77%
Provision Overlap Jaccard
0%
Outcome Match Categorical
100%
Subject Tags Jaccard
14%
Principle Tensions Jaccard
0%
What They Share

Topics: Advertising Misrepresentation/Omission of Facts

Citations: Case 76-4

Outcome: Both Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
60%
Discussion Similarity Cosine
53%
Provision Overlap Jaccard
12%
Outcome Match Categorical
100%
Subject Tags Jaccard
22%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.7

Topics: Public Statements and Criticism Unethical Practice by Others

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
58%
Discussion Similarity Cosine
55%
Provision Overlap Jaccard
10%
Outcome Match Categorical
100%
Subject Tags Jaccard
10%
Principle Tensions Jaccard
0%
What They Share

Provisions: II.5.a

Topics: Misrepresentation/Omission of Facts

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
49%
Discussion Similarity Cosine
45%
Provision Overlap Jaccard
15%
Outcome Match Categorical
100%
Subject Tags Jaccard
33%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.8.a III.9

Topics: Licensure Laws Advertising Credit for Engineering Work +1

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
42%
Discussion Similarity Cosine
60%
Provision Overlap Jaccard
0%
Outcome Match Categorical
100%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism Unethical Practice by Others Advertising +1

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
41%
Discussion Similarity Cosine
81%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Citations: Case 76-4

Outcome: None vs Unclear

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
58%
Discussion Similarity Cosine
56%
Provision Overlap Jaccard
0%
Outcome Match Categorical
50%
Subject Tags Jaccard
22%
Principle Tensions Jaccard
0%
What They Share

Topics: Public Statements and Criticism Misrepresentation/Omission of Facts

Outcome: None vs Mixed

Pattern: Both Stalemate

References View all

Richter, M.M. & Weber, R.O. (2013). Case-Based Reasoning: A Textbook. Springer. ISBN: 978-3-642-40166-4.

Reimers, N. & Gurevych, I. (2019). Sentence-BERT: Sentence embeddings using Siamese BERT-Networks. Proceedings of EMNLP-IJCNLP 2019, pp. 3982-3992. DOI: 10.18653/v1/D19-1410

Sun, Z., Zhang, K., Yu, W., Wang, H. & Xu, J. (2024). Logic rules as explanations for legal case retrieval. Proceedings of LREC-COLING 2024, pp. 10747-10759. ACL Anthology

Wiratunga, N., et al. (2024). CBR-RAG: Case-based reasoning for retrieval augmented generation in LLMs for legal question answering. arXiv preprint arXiv:2404.04302. arXiv