The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2001. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.
Management and performance of the bodies that make up the Judicial Branch of the Federation, as well as the Agrarian Courts, 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Federal Government Retirement Funds; Nonmarketable Treasury Securities Held by Judicial Retirement Fund; Asset, Transactions was 788.00000 Mil. of $ in January of 2025, according to the United States Federal Reserve. Historically, United States - Federal Government Retirement Funds; Nonmarketable Treasury Securities Held by Judicial Retirement Fund; Asset, Transactions reached a record high of 788.00000 in January of 2025 and a record low of -271.00000 in January of 2013. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Federal Government Retirement Funds; Nonmarketable Treasury Securities Held by Judicial Retirement Fund; Asset, Transactions - last updated from the United States Federal Reserve on July of 2025.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Federal Government Retirement Funds; Nonmarketable Treasury Securities Held by Judicial Retirement Fund; Asset, Level (BOGZ1FL343099050Q) from Q4 1945 to Q1 2025 about retirement, legal, Treasury, securities, federal, assets, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Government current expenditures: Federal: Public order and safety: Law courts was 9.49500 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government current expenditures: Federal: Public order and safety: Law courts reached a record high of 9.49500 in January of 2023 and a record low of 0.08200 in January of 1959. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government current expenditures: Federal: Public order and safety: Law courts - last updated from the United States Federal Reserve on July of 2025.
In the fiscal year of 2024, the budget for the Department of Health and Human Services amounted to **** trillion U.S. dollars. In comparison, the Small Business Administration is expected to have a budget of ***** billion U.S. dollars. United States Federal Government The federal government in the United States consists of three branches of the government: the legislative, executive, and judicial branches. The executive branch is the office of the President of the United States, the legislative branch is the United States Congress, and the judicial branch is the United States Supreme Court.The U.S. cabinet belongs to the executive branch of the government, which belongs to the president and vice president. U.S. Department of Health and Human Services The U.S. Department of Health and Human Services is the department of the federal government that provides health services to Americans. The Secretary of the department is Xavier Becerra, who was appointed by current president Joe Biden. Some of the Operating Divisions in this department include the Food and Drug Administration, the Center for Disease Control and Prevention, and the National Institutes of Health. The outlays for the Department of Health and Human Services have been steadily increasing since 2000. The agency that had the highest amount of spending in this department in 2024 was the Centers of Medicare and Medicaid Services.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Employed full time: Wage and salary workers: Judicial law clerks occupations: 16 years and over: Men was 8.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Judicial law clerks occupations: 16 years and over: Men reached a record high of 8.00000 in January of 2024 and a record low of 1.00000 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Judicial law clerks occupations: 16 years and over: Men - last updated from the United States Federal Reserve on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Employed full time: Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over was 51.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over reached a record high of 73.00000 in January of 2005 and a record low of 41.00000 in January of 2002. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over - last updated from the United States Federal Reserve on July of 2025.
https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy
According to Cognitive Market Research, the global Legal Ai Software market size is USD 1151.2million in 2023 and will expand at a compound annual growth rate (CAGR) of 32.50% from 2023 to 2030.
North America held the major market of more than 40% of the global revenue with a market size of USD 460.48 million in 2023 and will grow at a compound annual growth rate (CAGR) of 30.7% from 2023 to 2030
Europe market of more than 30% of the global revenue with a market size of USD 345.36 million in 2023 and will grow at a compound annual growth rate (CAGR) of 31.0% from 2023 to 2030
Asia-Pacific held the fastest market of more than 23% of the global revenue with a market size of USD 264.78 million in 2023 and will grow at a compound annual growth rate (CAGR) of 34.5% from 2023 to 2030.
Latin American market of more than 5% of the global revenue with a market size of USD 57.56 million in 2023 and will grow at a compound annual growth rate (CAGR) of 31.9% from 2023 to 2030
Middle East and Africa market of more than 2.00% of the global revenue with a market size of USD 23.02 million in 2023 and will grow at a compound annual growth rate (CAGR) of 32.2% from 2023 to 2030
The demand for Legal Ai Software is rising due to the increased legal process efficiency and rising demand for advanced analytics and predictive tools..
Demand for eDiscovery remains higher in the Legal Ai Software market.
The Solutions category held the highest Legal Ai Software market revenue share in 2023.
Automation of Legal Processes to Provide Viable Market Output
The Legal AI Software market is driven by the increasing demand for automation in legal processes. Legal professionals face the challenge of managing vast amounts of data, documents, and contracts. AI-powered solutions enable the automation of routine tasks such as document review, contract analysis, and legal research. By leveraging machine learning algorithms, these tools enhance efficiency, reduce human error, and allow legal professionals to focus on higher-value, strategic aspects of their work. The drive for process optimization and time efficiency propels the adoption of Legal AI Software across law firms and legal departments.
May 2023 - Luminance Technologies Ltd has launched the latest cutting-edge application of its specialist legal large language model (LLM), the AI-powered 'Ask Lumi' chatbot. 'Ask Lumi' represents the first chatbot underpinned by this legal-grade AI.
(Source:www.luminance.com/news/press/20230511_luminance_announces.html)
Enhanced Legal Research and Analysis to Propel Market Growth
Legal AI Software plays a pivotal role in revolutionizing legal research and analysis. With the vast volume of legal information available, professionals need advanced tools to sift through data, extract relevant insights, and stay updated on evolving regulations. AI algorithms enable sophisticated legal research by quickly identifying relevant cases, statutes, and precedents. This capability enhances the speed and accuracy of legal analysis, empowering legal practitioners to make informed decisions. The demand for solutions that streamline legal research processes and provide actionable intelligence contributes significantly to the growth of the Legal AI Software market.
May 2023 - LexisNexis Group Inc has launched its highly-demanded API for state court Legal Analytics. where the customers can access Lex Machina's state court analytics and data directly through its API, enabling greater incorporation of Lex Machina's superior Legal Analytics directly into one seamless, existing workflow and with Lex Machina's new API for state courts, users can combine their internal data with Lex Machina's superior Legal Analytics for state courts as well as federal courts.
Market Restraints of the Legal AI Software
Ethical and Regulatory Challenges to Restrict Market Growth
The Legal AI Software market faces challenges associated with ethical considerations and regulatory compliance. As AI tools become integral to legal processes, concerns regarding data privacy, bias in algorithms, and the ethical use of AI in decision-making processes have emerged. Legal professionals need to navigate a complex landscape of regulations to ensure that AI applications adhere to ethical standards and legal requirements....
https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
The Legal AI Software market is experiencing robust growth, projected to reach $2.19 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 10.70% from 2025 to 2033. This expansion is driven by several key factors. The increasing volume and complexity of legal data necessitate efficient solutions for tasks such as contract review, e-discovery, and legal research. Law firms and corporate legal departments are increasingly adopting AI-powered tools to improve productivity, reduce operational costs, and enhance accuracy. Furthermore, the growing awareness of AI's potential to improve compliance and risk management is fueling market adoption. The cloud-based deployment model is witnessing significant traction due to its scalability, accessibility, and cost-effectiveness, contributing significantly to market growth. Leading vendors like Luminance Technologies, Ross Intelligence, and Kira Systems are continuously innovating, providing advanced solutions catering to various legal needs, further driving market expansion. Competition among established players and new entrants is fostering innovation and driving down prices, making AI-powered legal solutions more accessible to a wider range of users. The market segmentation reveals a diverse landscape. Solutions and services constitute the core components, with cloud deployment gaining significant momentum. Applications like legal research, contract review, and e-discovery remain dominant, although applications like case prediction are experiencing rapid growth as AI capabilities mature. Law firms are the largest end-users, followed by corporate legal departments. While North America currently holds the largest market share due to early adoption and a robust technological infrastructure, the Asia-Pacific region is projected to experience significant growth in the coming years driven by increasing digitalization and economic growth. The market faces challenges such as concerns around data security and the need for substantial initial investments, but the overall positive growth trajectory suggests a bright future for Legal AI software. Recent developments include: May 2023 - LexisNexis Group Inc has launched its highly-demanded API for state court Legal Analytics. where the customers can access Lex Machina's state court analytics and data directly through its API, enabling greater incorporation of Lex Machina's superior Legal Analytics directly into one seamless, existing workflow and with Lex Machina's new API for state courts, users can combine their internal data with Lex Machina's superior Legal Analytics for state courts as well as federal courts., April 2023 - Luminance Technologies Ltd has announced that it has partnered with alternative service legal provider, Nexa, to embed Luminance's next-generation AI into the NexaConnex legal service offering, where by embedding Luminance's next-generation AI into their offering, NexaConnex's clients will be able to drive much-needed efficiencies into their day-to-day work and dedicate more time to high-value client activities.. Key drivers for this market are: Growing Demand For Automation And Increasing Number Of Litigations In The Legal Industry, Growth In The Utilization Of AI By Legal Companies To Complete Legal Cases. Potential restraints include: Growing Demand For Automation And Increasing Number Of Litigations In The Legal Industry, Growth In The Utilization Of AI By Legal Companies To Complete Legal Cases. Notable trends are: Cloud is Expected to Hold Significant Share.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Government consumption expenditures and gross investments: Federal: Public order and safety: Law courts was 11.00000 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government consumption expenditures and gross investments: Federal: Public order and safety: Law courts reached a record high of 11.00000 in January of 2023 and a record low of 0.07800 in January of 1959. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government consumption expenditures and gross investments: Federal: Public order and safety: Law courts - last updated from the United States Federal Reserve on July of 2025.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Das Corpus der Entscheidungen des Bundesfinanzhofs (CE-BFH) ist eine möglichst vollständige Sammlung der vom Bundesfinanzhof (BFH) veröffentlichten Entscheidungen. Der Datensatz nutzt als seine Datenquelle die amtliche Entscheidungsdatenbank des Bundesfinanzhofs und wertet diese vollständig aus.
Bitte lesen Sie zuerst das beiliegende Codebook! Es enthält wichtige Informationen zur korrekten Nutzung des Datensatzes. Es hilft auch bei der Entscheidung, welche Variante für Sie am besten geeignet ist. In der Regel empfehle ich für quantitative Forschung die CSV-Dateien und für traditionelle Forschung die PDF-Sammlung.
Für Praktiker:innen stelle ich zusätzlich eine Variante mit allen in der amtlichen Sammlung BFHE abgedruckten "V-Entscheidungen" zur Verfügung.
Dieser Datensatz wird 1-2 mal im Jahr aktualisiert. Benachrichtigungen über neue und aktualisierte Datensätze veröffentliche ich immer zeitnah auf Mastodon unter @seanfobbe@fediscience.org
Stichtag: 14. Januar 2025
Inhaltlicher Umfang: 10.885 Entscheidungen des Bundesfinanzhofs der Bundesrepublik Deutschland
Zeitlicher Umfang: ab Januar 2010 bis zum Stichtag
Formate: CSV, GraphML, PDF, TXT und HTML
Der gesamte Erstellungs-Prozess ist vollautomatisiert und detailliert dokumentiert. Mit jeder Kompilierung des vollständigen Datensatzes wird auch ein umfangreicher Compilation Report in einem attraktiv designten PDF-Format erstellt (ähnlich dem Codebook). Zudem werden Robustness Checks auf Vollständigkeit und Plausibilität durchgeführt und in einem separaten Bericht dokumentiert.
Der Compilation Report enthält den Code für die vollständige Pipeline, dokumentiert relevante Rechenergebnisse, gibt sekundengenaue Zeitstempel an und ist mit einem klickbaren Inhaltsverzeichnis versehen. Er ist zusammen mit dem Source Code hinterlegt. Wenn Sie sich für Details des Erstellungs-Prozesses interessieren, lesen Sie diesen bitte zuerst.
Der vollständige Source Code — sowohl für die Erstellung des Datensatzes, als auch für das Codebook — ist öffentlich einsehbar und dauerhaft erreichbar im wissenschaftlichen Archiv des CERN unter diesem Link hinterlegt: https://doi.org/10.5281/zenodo.7691842
Die Integrität und Echtheit der einzelnen Archive des Datensatzes sind durch eine Zwei-Phasen-Signatur sichergestellt.
In Phase I werden während der Kompilierung für jedes ZIP-Archiv, das Codebook und die Robustness Checks Hash-Werte in zwei verschiedenen Verfahren (SHA2-256 und SHA3-512) berechnet und in einer CSV-Datei dokumentiert.
In Phase II werden diese CSV-Datei und der Compilation Report mit meinem persönlichen geheimen GPG-Schlüssel signiert. Dieses Verfahren stellt sicher, dass die Kompilierung von jedermann durchgeführt werden kann, insbesondere im Rahmen von Replikationen, die persönliche Gewähr für Ergebnisse aber dennoch vorhanden ist.
Die während der Kompilierung des Datensatzes erstellte CSV-Datei mit den Hash-Prüfsummen ist mit meiner persönlichen GPG-Signatur versehen. Der mit dieser Version korrespondierende Public Key ist sowohl mit dem Datensatz als auch mit dem Source Code hinterlegt. Er hat folgende Kenndaten:
Name: Sean Fobbe (fobbe-data@posteo.de)
Fingerabdruck: FE6F B888 F0E5 656C 1D25 3B9A 50C4 1384 F44A 4E42
An den Entscheidungen und Metadaten besteht gem. § 5 Abs. 1 UrhG kein Urheberrecht, da sie amtliche Werke sind. § 5 UrhG ist auf amtliche Datenbanken analog anzuwenden (BGH, Beschluss vom 28.09.2006 - I ZR 261/03, "Sächsischer Ausschreibungsdienst"). Alle eigenen Beiträge (z.B. durch Zusammenstellung und Anpassung der Metadaten) und damit den gesamten Datensatz stelle ich gemäß einer CC0 1.0 Universal Public Domain License vollständig urheberrechtsfrei.
Dieser Datensatz ist eine private wissenschaftliche Initiative und steht in keiner Verbindung zu Behörden, Gerichten oder anderen öffentlichen Stellen der Bundesrepublik Deutschland.
Website — www.seanfobbe.de
Open Data — zenodo.org/communities/sean-fobbe-data/
Source Code — zenodo.org/communities/sean-fobbe-code/
Volltexte regulärer Publikationen — zenodo.org/communities/sean-fobbe-publications/
Fehler gefunden? Anregungen? Melden Sie diese entweder im Issue Tracker auf GitHub oder schreiben Sie mir eine E-Mail an fobbe-data@posteo.de
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
A federal judge has paused the Arizona land transfer for a copper mine project by Rio Tinto and BHP, amid Native American opposition and pending a Supreme Court review.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over was 2307.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over reached a record high of 2307.00000 in January of 2024 and a record low of 1101.00000 in January of 2005. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Judges, magistrates, and other judicial workers occupations: 16 years and over - last updated from the United States Federal Reserve on August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Total Revenue for Court Reporting and Stenotype Services, Establishments Subject to Federal Income Tax, Employer Firms was 3653.00000 Mil. of $ in January of 2022, according to the United States Federal Reserve. Historically, United States - Total Revenue for Court Reporting and Stenotype Services, Establishments Subject to Federal Income Tax, Employer Firms reached a record high of 3653.00000 in January of 2022 and a record low of 1050.00000 in January of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Total Revenue for Court Reporting and Stenotype Services, Establishments Subject to Federal Income Tax, Employer Firms - last updated from the United States Federal Reserve on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Equity Market Volatility Tracker: Lawsuit And Tort Reform Supreme Court Decisions was 1.58294 Index in May of 2025, according to the United States Federal Reserve. Historically, United States - Equity Market Volatility Tracker: Lawsuit And Tort Reform Supreme Court Decisions reached a record high of 3.03719 in December of 2000 and a record low of 0.00000 in August of 1985. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Equity Market Volatility Tracker: Lawsuit And Tort Reform Supreme Court Decisions - last updated from the United States Federal Reserve on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Government current expenditures: State and local: Public order and safety: Law courts was 67.19700 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government current expenditures: State and local: Public order and safety: Law courts reached a record high of 67.19700 in January of 2023 and a record low of 0.58600 in January of 1959. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government current expenditures: State and local: Public order and safety: Law courts - last updated from the United States Federal Reserve on August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Government consumption expenditures and gross investments: State and local: Public order and safety: Law courts was 69.07400 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government consumption expenditures and gross investments: State and local: Public order and safety: Law courts reached a record high of 69.07400 in January of 2023 and a record low of 0.59900 in January of 1959. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government consumption expenditures and gross investments: State and local: Public order and safety: Law courts - last updated from the United States Federal Reserve on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Total Revenue for Court Reporting and Stenotype Services, All Establishments, Employer Firms was 3653.00000 Mil. of $ in January of 2022, according to the United States Federal Reserve. Historically, United States - Total Revenue for Court Reporting and Stenotype Services, All Establishments, Employer Firms reached a record high of 3653.00000 in January of 2022 and a record low of 1050.00000 in January of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Total Revenue for Court Reporting and Stenotype Services, All Establishments, Employer Firms - last updated from the United States Federal Reserve on August of 2025.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Equity Market Volatility Tracker: Lawsuit And Tort Reform Supreme Court Decisions (EMVLAWTORT) from Jan 1985 to Jul 2025 about legal, volatility, uncertainty, equity, and USA.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2001. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.