Longitudinal Collection of UK County Court Daily Hearing Lists

Purpose and Global Accessibility This project provides an independent archive to support Access to Justice for the public, including researchers, NGOs, and the growing number of self-represented parties, i.e. Litigants in Person (LIPs) also known as pro-se litigants, globally. By offering this data in a machine-readable format (pipe-separated, fixed width) with comparative terminology, the project ensures that practices, patterns and allocation of time in County Courts remain in the public domain and inform applications, decision-making processes and related complaints processes, as well as appeals or actions required to address irregularities. Governance and Funding The research project has been independently conceived, designed, and executed, including all necessary personal funding for data acquisition and processing. The project maintains full autonomy over the research agenda, data interpretation, and final outputs. Human-AI Collaborative Framework To ensure methodological rigour and reduce potential cognitive bias, a hybrid workflow integrating Large Language Models (LLMs) alongside traditional data analysis tools was employed. This collaboration was structured as an iterative, Agile-based review cycle, where AI assisted in: Data Aggregation: Consolidating raw listings from multiple County Courts, including Central London, Wandsworth, and Clerkenwell & Shoreditch into standardised, fixed-width plain text tables. Trend Identification: Recognising longitudinal patterns, such as the regular bi-monthly processing of "Restored Name" applications and the consistency of "HMRC Petitions" peaks. Verification: Cross-referencing AI-generated subtotals against source records to ensure accuracy in unique case reference counts and hearing channel classifications (e.g., In Person, CVP / MS Teams, Telephone, and On the Papers). By consolidating data from July 2025 through April 2026, this archive serves as a public resource for researchers, litigants, NGOs and other parties globally. Case management patterns vary, depending on the allocated track (based on case value in £/GBP) and judicial allocation of time. Judicial determinations "On the Papers" permit maximum flexibility as they do not require parties in attendance. The dataset makes this granular, anonymised data transparent and searchable beyond the fragmented official portals which override daily listings. Disclaimer: The comparative legal terminology provided here, and all other information within this dataset and research project, is for archival and informational purposes only. It does not constitute legal advice, legal strategy, or financial advice. Methodology: This dataset consists of data extracted and synthesised from official UK County Court Daily Hearing / Cause Lists (July 2025 – April 2026). The primary source data are not included in this repository to respect the terms of the original listing services. The data has been transformed into a structured format to facilitate longitudinal analysis of hearing types, and the use of remote hearing channels including video, telephone and on the papers. Distinct Entities: It distinguishes between the total number of entries and the number of specific, separate categories. For instance, while there are hundreds of individual hearings, they only occupy five unique channels, i.e. In person, MS Teams / CVP, On the Papers, and Telephone. Methodological Rigour: Using "unique" ensures counting of discrete variables rather than raw instances. The sources themselves adopt this terminology, specifically defining "Count" as the total number of "unique case reference numbers" to avoid double-counting the same legal matter in aggregated summaries. Longitudinal Accuracy: Across the various date ranges - from July 2025 through April 2026 - certain courts or types appear repeatedly. Identifying the unique count (e.g., six courts) provides exactly how many distinct venues are being monitored regardless of how many times they appear in the data. Technical specification Standardised `.txt` File Format Specification to ensure the dataset is machine-readable and archival-grade. Structural rules applied: 1. Fixed-Width Layout - Structure: Uses a fixed-width plain text table where each column has a consistent character count. - Separator: Uses the pipe symbol (`|`) between headers and data columns to facilitate future conversion to CSV or database formats. - Headers: Uses exactly these six column headers: `DATE | COURT NAME | HEARING TYPE | CATEGORY | CHANNEL | COUNT` 2. Column Definitions - DATE: DD/MM/YYYY. - COURT NAME: The full name of the court (e.g., Central London, Wandsworth). - HEARING TYPE: The primary description of the hearing (e.g., Application, Trial). - CATEGORY: The bracketed legal classification found in the source (e.g., [PCOL], [Small Claim]). Uses `[N/A]` if not present. - CHANNEL: The mode of appearance (e.g., In person, MS Teams / CVP [Cloud Video Platform], On the Papers). - COUNT: The total number of unique case reference numbers listed for that specific row profile. 3. Privacy and Anonymisation - No Personal Data: Removed were all names of Judges, District Judges, Clerks, Ushers, and Parties. - Data Aggregation: Only includes counts of cases per hearing profile; does not list individual case names or numbers. 4. Asterisked Comments (Footer) Qualitative administrative metadata that does not fit into the table has been placed at the bottom of the file using a single or double asterisk system (**) ### **Standardized Template** ```text DATE | COURT NAME | HEARING TYPE | CATEGORY | CHANNEL | COUNT ------------------------------------------------------------------------------------------------------------- DD/MM/YYYY | [Full Court Name] | [Type of Hearing] | [Tag] | [In person/Remote]| 0 ------------------------------------------------------------------------------------------------------------- TOTAL FOR DATE 0 * [Comment regarding specific administrative list or venue] ** [Comment regarding specific officer or listing anomaly]### 项目宗旨与全球可及性 本项目打造独立档案库，旨在为全球公众（包括研究人员、非政府组织，以及日益增多的自行代理诉讼方——即无律师代理诉讼人（Litigants in Person, LIPs），亦称自诉当事人）提供司法救助支持。 本项目以机器可读格式（管道分隔、固定宽度）并辅以对比术语发布数据，确保郡法院的诉讼实践、流程模式与时间分配均处于公共领域，可为相关申请、决策流程及投诉流程，以及应对违规行为所需的上诉或法律行动提供参考依据。 ### 治理与资金来源 本研究项目由团队独立构思、设计并执行，数据获取与处理所需的全部必要个人资金均由团队自筹。本项目在研究议程、数据解读与最终成果方面拥有完全自主权。 ### 人机协同框架 为确保方法学严谨性并降低潜在认知偏差，本项目采用融合大语言模型（Large Language Models, LLMs）与传统数据分析工具的混合工作流。该协作以迭代式、基于敏捷方法的审查周期构建，AI辅助完成以下工作： 1. **数据聚合**：整合来自伦敦中央、旺兹沃思以及克拉彭与肖尔迪奇等多家郡法院的原始庭审清单，将其整合为标准化的固定宽度纯文本表格。 2. **趋势识别**：识别纵向模式，例如“恢复姓名”申请的每两个月一次的常规处理流程，以及“HMRC请愿书”峰值的一致性。 3. **核验**：将AI生成的小计与源记录交叉比对，确保唯一案件编号计数与庭审渠道分类（例如线下庭审、CVP/MS Teams线上庭审、电话庭审以及书面审理）的准确性。 本项目整合2025年7月至2026年4月的数据，打造面向全球研究人员、诉讼当事人、非政府组织及其他相关方的公共资源。 案件管理模式因分配的诉讼程序轨道（基于案件价值，以英镑计价）与法官分配的时间而异。“书面审理”的司法裁决可实现最大灵活性，因为无需当事人到场。本数据集将此类细粒度的匿名数据透明化并开放检索，弥补了碎片化官方门户网站仅能展示当日庭审清单的局限。 ### 免责声明 本数据集及研究项目中提供的对比法律术语与所有其他信息，仅用于档案存储与信息参考，不构成法律建议、法律策略或财务建议。 ### 研究方法 本数据集提取自英国郡法院官方每日庭审/案件清单（2025年7月至2026年4月）并进行综合处理。为尊重原始清单服务的使用条款，本仓库未包含原始源数据。 数据已转换为结构化格式，以支持对庭审类型及远程庭审渠道（包括视频、电话及书面审理）的纵向分析。 #### 实体区分 本数据集区分条目总数与特定独立类别的数量。例如，尽管存在数百个独立庭审，但仅对应五种独特的庭审渠道，即线下庭审、MS Teams/CVP、书面审理以及电话庭审。 #### 方法学严谨性 采用“唯一值”计数可确保对离散变量而非原始实例进行统计。源数据本身即采用该术语，明确将“计数（Count）”定义为“唯一案件编号”的总数，以避免在聚合汇总中重复统计同一法律事项。 #### 纵向准确性 在2025年7月至2026年4月的各个日期范围内，部分法院或案件类型会重复出现。通过统计唯一计数（例如6家法院），可明确显示被监测的不同庭审场所的实际数量，而非其在数据中出现的次数。 ### 技术规范 本数据集采用标准化`.txt`文件格式，确保其具备机器可读性与档案级存储标准。应用的结构规则如下： 1. **固定宽度布局** - 结构：采用固定宽度纯文本表格，每列拥有固定字符数。 - 分隔符：在表头与数据列之间使用管道符号（`|`），便于后续转换为CSV或数据库格式。 - 表头：严格使用以下六个列标题： text DATE | COURT NAME | HEARING TYPE | CATEGORY | CHANNEL | COUNT 2. **列定义** - DATE：格式为DD/MM/YYYY（日/月/年）。 - COURT NAME：法院全称（例如伦敦中央、旺兹沃思）。 - HEARING TYPE：庭审的核心描述（例如申请、庭审）。 - CATEGORY：源数据中带括号的法律分类（例如[PCOL]、[小额索赔]）。若无分类，则使用`[N/A]`。 - CHANNEL：庭审参与方式（例如线下庭审、MS Teams/CVP（云视频平台，Cloud Video Platform）、书面审理）。 - COUNT：对应特定行配置的唯一案件编号的总数量。 3. **隐私与匿名化** - 无个人数据：已移除所有法官、地区法官、书记员、庭警以及诉讼当事人的姓名。 - 数据聚合：仅包含按庭审配置统计的案件数量，未列出单个案件的名称或编号。 4. **带星号的注释（页脚）** 无法纳入表格的定性行政元数据，将通过单星号或双星号（`**`）系统置于文件底部。 ### 标准化模板 text DATE | COURT NAME | HEARING TYPE | CATEGORY | CHANNEL | COUNT ------------------------------------------------------------------------------------------------------------- DD/MM/YYYY | [Full Court Name] | [Type of Hearing] | [Tag] | [In person/Remote]| 0 ------------------------------------------------------------------------------------------------------------- TOTAL FOR DATE 0 * [针对特定行政清单或庭审场所的注释] ** [针对特定工作人员或清单异常的注释]