/*  (ssrn-4962098) — corpus code wrapper This file intentionally embeds the paper text and study assets in code form. It helps code-centric ingestion pipelines and makes the corpus easy to load programmatically. */ #include #include #include namespace my_works_for_llm { static const char* PAPER_ID = "ssrn-4962098"; static const std::string TITLE = R"MW4LLM()MW4LLM"; static const std::string SSRN_URL = R"MW4LLM(https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4962098)MW4LLM"; static const int YEAR = 2024; static const std::vector AUTHORS = {"Yonathan Arbel"}; static const std::vector KEYWORDS = {"contracts", "AI", "law"}; static const std::string SUMMARY_MD = R"MW4LLM(Here is the bullet list for "The Readability of Contracts: A Big Data Analysis" (ssrn-4962098) by Professor Yonathan Arbel: * ## TL;DR Professor Yonathan Arbel of the University of Alabama School of Law argues that his large-scale big data analysis empirically demonstrates modern contracts are overwhelmingly unreadable, often requiring college-level comprehension. This pervasive incomprehensibility fundamentally challenges contract law's core assumptions about informed consent and the "meeting of minds," as most individuals cannot understand the terms binding them. Arbel suggests this "readability crisis," with readability often worsening over time, necessitates a reevaluation of legal doctrines and a push for greater contractual clarity to ensure fairness and true agreement in economic and social interactions. * ## Section Summaries * **Introduction and Problem Definition:** Professor Yonathan Arbel of the University of Alabama School of Law writes that his research presents the first large-scale empirical study of contract readability, addressing their notorious unreadability and how it challenges core assumptions of contract law like informed consent. He writes that despite contracts being foundational, their pervasive unreadability means most individuals do not understand the terms they are bound by, a "unreadability crisis" that his big data analysis aims to systematically quantify, revealing that contracts are substantially less readable than other texts and have worsened over time, especially for consumer contracts, undermining consumer trust and welfare. * **Theoretical Framework and Hypotheses:** Professor Yonathan Arbel of the University of Alabama School of Law writes that the pervasive unreadability of contracts presents a puzzle, with common explanations including lawyers' rent-seeking behaviors, the inherent complexity of legal concepts, or a rational desire for precision and risk mitigation. He writes that his research explores hypotheses that overall contract readability has not significantly improved, and that consumer contracts in particular exhibit lower readability due to information asymmetries and the strategic use of boilerplate, challenging the notion that complexity is always necessary or solely benefits sophisticated parties. * **Methodology and Data:** Professor Yonathan Arbel of the University of Alabama School of Law writes that his study employs a big data approach, utilizing an expansive and diverse dataset of over 1.2 million contracts sourced from public repositories like the SEC’s EDGAR database and the Consumer Financial Protection Bureau’s (CFPB) database, covering a wide variety of agreement types. He writes that these contracts underwent extensive cleaning to isolate substantive provisions for analysis using established readability metrics, primarily focusing on Flesch Reading Ease and Flesch-Kincaid Grade Level scores, chosen for their prevalence and validation as useful proxies for textual difficulty. * **Empirical Findings on Contract Readability:** Professor Yonathan Arbel of the University of Alabama School of Law writes that his large-scale empirical analysis reveals a significant "readability crisis," with most contracts written at a level far exceeding the comprehension abilities of the average American adult, often requiring a college-level education or higher. He writes that this profound unreadability, driven by complex sentence structures, excessive length, and dense legal jargon, has often worsened over time across various contract types. This means contracts frequently fail to provide meaningful notice of their terms, challenging the foundational notion of mutual assent, as consumers overwhelmingly do not read or cannot understand them. * **Discussion, Implications, and Conclusion:** Professor Yonathan Arbel of the University of Alabama School of Law writes that pervasive contract unreadability inflates transaction costs for consumers, creates information asymmetries detrimental to them, and fundamentally undermines the ideal of informed consent, suggesting low readability may serve strategic purposes for drafters or stem from systemic issues like path dependency. He writes that enhancing contract readability is a crucial policy objective, potentially achievable through better drafting practices, technological aids like AI-powered summaries, or regulatory interventions setting readability standards. This "comprehension chasm" calls for a reevaluation of legal doctrines and a new, empirically-grounded realism in contract law.)MW4LLM"; static const std::string SUMMARY_ZH_MD = R"MW4LLM(好的，这是对您提供的英文法律摘要的正式中文翻译： **《合同可读性：一项大数据分析》（SSRN-4962098），作者：约纳森·阿尔贝教授** * ## 核心观点阿拉巴马大学法学院的约纳森·阿尔贝（Yonathan Arbel）教授指出，其大规模大数据分析实证表明，现代合同绝大多数难以卒读，通常需要达到大学文化程度的理解水平。这种普遍存在的晦涩难懂现象，从根本上挑战了合同法关于知情同意和“意思表示一致”的核心假设，因为大多数人无法理解约束他们的条款。阿尔贝教授认为，这种“可读性危机”（且合同可读性常随时间推移而恶化）使得有必要重新评估相关法律原则，并推动提高合同的清晰度，以确保经济和社会交往中的公平与真实合意。 * ## 各章节摘要 * **引言与问题界定：** 阿拉巴马大学法学院的约纳森·阿尔贝教授写道，其研究首次对合同可读性进行了大规模实证考察，旨在探讨合同普遍存在的晦涩难懂问题及其如何挑战合同法中如“知情同意”等核心假设。他指出，尽管合同是基础性法律文件，但其普遍的不可读性意味着大多数个体无法理解约束他们的条款，这构成了“可读性危机”。他的大数据分析旨在系统地量化此问题，揭示了合同的可读性远低于其他文本，并且随着时间的推移而恶化，尤其是在消费者合同中，这损害了消费者的信任和福祉。 * **理论框架与假设：** 阿拉巴马大学法学院的约纳森·阿尔贝教授写道，合同普遍存在的不可读性构成了一个难题，常见的解释包括律师的寻租行为、法律概念固有的复杂性，或对精确性和风险规避的理性追求。他指出，其研究探讨了以下假设：合同的整体可读性并未显著改善，特别是消费者合同，由于信息不对称和格式条款的策略性使用，其可读性更低，这挑战了复杂性总是必要的或仅有利于成熟老练一方的观点。 * **研究方法与数据：** 阿拉巴马大学法学院的约纳森·阿尔贝教授写道，其研究采用大数据方法，使用了来自美国证券交易委员会（SEC）的EDGAR数据库和消费者金融保护局（CFPB）数据库等公共存储库的超过120万份合同，构成了一个广泛且多样化的数据集，涵盖了多种协议类型。他指出，这些合同经过了大量清理工作，以分离出实质性条款，并使用成熟的可读性指标进行分析，主要集中在弗莱施阅读易读性（Flesch Reading Ease）和弗莱施-金凯德年级水平（Flesch-Kincaid Grade Level）评分，选择这些指标是因为它们的普遍性以及作为文本难度有效替代指标的验证。 * **合同可读性的实证研究发现：** 阿拉巴马大学法学院的约纳森·阿尔贝教授写道，其大规模实证分析揭示了严重的“可读性危机”，大多数合同的撰写水平均远超美国普通成年人的理解能力，通常需要大学或更高学历水平。他指出，这种由复杂句式结构、过长篇幅和密集法律术语导致的深度不可读性，在各类合同中常随时间推移而恶化。这意味着合同常常无法就其条款提供有意义的通知，挑战了双方合意的基本概念，因为消费者绝大多数不阅读或无法理解这些合同。 * **讨论、影响与结论：** 阿拉巴马大学法学院的约纳森·阿尔贝教授写道，普遍存在的合同不可读性增加了消费者的交易成本，造成了对消费者不利的信息不对称，并从根本上削弱了知情同意的理想状态，表明低可读性可能服务于起草方的策略性目的，或源于路径依赖等系统性问题。他指出，提高合同可读性是一项关键的政策目标，可能通过改进起草实践、人工智能驱动的摘要等技术辅助手段，或设定可读性标准的监管干预来实现。这种“理解鸿沟”要求对法律原则进行重新评估，并在合同法中引入一种新的、基于实证的现实主义。)MW4LLM"; static const std::string ONE_PAGER_MD = R"MW4LLM(#  — one-page summary **Paper ID:** `ssrn-4962098` **Year:** 2024 **Author(s):** Yonathan Arbel **SSRN:** https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4962098 ## TL;DR Professor Yonathan Arbel of the University of Alabama School of Law argues that his large-scale big data analysis empirically demonstrates modern contracts are overwhelmingly unreadable, often requiring college-level comprehension. This pervasive incomprehensibility fundamentally challenges contract law's core assumptions about informed consent and the "meeting of minds," as most individuals cannot understand the terms binding them. Arbel suggests this "readability crisis," with readability often worsening over time, necessitates a reevaluation of legal doctrines and a push for greater contractual clarity to ensure fairness and true agreement in economic and social interactions. ## Keywords contracts; AI; law ## Files - Full text: `papers/ssrn-4962098/paper.txt` - PDF: `papers/ssrn-4962098/paper.pdf` - Summary (EN): `papers/ssrn-4962098/summary.md` - Summary (ZH): `papers/ssrn-4962098/summary.zh.md` _Auto-generated study aid. For canonical content, rely on `paper.txt`/`paper.pdf`._ )MW4LLM"; static const std::string STUDY_PACK_MD = R"MW4LLM(# Study pack:  (ssrn-4962098) - SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4962098 - Full text: `papers/ssrn-4962098/paper.txt` - Summary (EN): `papers/ssrn-4962098/summary.md` - Summary (ZH): `papers/ssrn-4962098/summary.zh.md` ## Elevator pitch Professor Yonathan Arbel of the University of Alabama School of Law argues that his large-scale big data analysis empirically demonstrates modern contracts are overwhelmingly unreadable, often requiring college-level comprehension. This pervasive incomprehensibility fundamentally challenges contract law's core assumptions about informed consent and the "meeting of minds," as most individuals cannot understand the terms binding them. Arbel suggests this "readability crisis," with readability often worsening over time, necessitates a reevaluation of legal doctrines and a push for greater contractual clarity to ensure fairness and true agreement in economic and social interactions. ## Keywords / concepts contracts; AI; law ## Suggested questions (for RAG / study) - What is the paper’s main claim and what problem does it solve? - What method/data does it use (if any), and what are the main results? - What assumptions are doing the most work? - What are the limitations or failure modes the author flags? - How does this connect to the author’s other papers in this corpus? _Auto-generated study aid. For canonical content, rely on `paper.txt`/`paper.pdf`._ )MW4LLM"; static const std::string ARTICLE_TEXT = R"MW4LLM( <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 2/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 3/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 4/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 5/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 6/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 7/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 8/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 9/55 ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 10/55 𝔼(𝑆 −𝑆 𝑚𝑎𝑥 min⁡) <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 11/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 12/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 13/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 14/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 15/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 16/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 17/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 18/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 19/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 20/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 21/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 22/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 23/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 24/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 25/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 26/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 27/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 28/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 29/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 30/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 31/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 32/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 33/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 34/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 35/55 CRM Flesch Kincaid Contract Type % % 2001 2022 2001 2022 Change Change Non-Competes, Confidentiality, - - 14.5 16.5 15.9 18.5 & Post- 13.80% 16.40% Employment Insurance, - - Indemnity, and 17 19.2 18.5 25.1 13.00% 35.50% Coverage Ownership, - Trust, and 16.5 18.1 -9.70% 18.9 23.2 23.30% Governance Mergers, Alliance, and - 16.2 17.7 -9.30% 18.9 22.2 Investment 18.70% Agreements Shares, Stocks, - Incentives, and 15.6 17.2 -9.90% 17.4 19.3 10.90% Options Credit, Debt, - and Security 16.4 17.7 -7.90% 18.8 22.3 18.60% Agreements Property, - 16 17.2 -7.50% 18.1 20.9 Rights, and IP 15.50% Purchase or - Sale 16.2 17.3 -6.80% 18.3 21 14.80% Agreement Settlement, Waiver, and 16.6 17.6 -6.00% 19.3 20.9 -8.30% Termination or Severance Employment 16.4 17.2 -4.90% 18.7 20 -7.00% Agreement Services & 15.3 15.2 -0.7% 16.5 17.4 -5.50% Supply <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 36/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 37/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 38/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 39/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 40/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 41/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 42/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 43/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 44/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 45/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 46/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 47/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 48/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 49/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 50/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 51/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 52/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 53/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 54/55 <> ARBEL, THE READABILITY OF CONTRACTS: BIG DATA ANALYSIS 55/55)MW4LLM"; struct Paper { std::string paper_id; std::string title; std::string ssrn_url; int year; std::vector authors; std::vector keywords; std::string summary_md; std::string summary_zh_md; std::string one_pager_md; std::string study_pack_md; std::string article_text; }; inline Paper as_paper() { return Paper{ PAPER_ID, TITLE, SSRN_URL, YEAR, AUTHORS, KEYWORDS, SUMMARY_MD, SUMMARY_ZH_MD, ONE_PAGER_MD, STUDY_PACK_MD, ARTICLE_TEXT}; } } // namespace my_works_for_llm int main(int argc, char** argv) { (void)argc; (void)argv; std::cout << my_works_for_llm::ARTICLE_TEXT; return 0; }