The Resource Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors
Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors
Resource Information
The item Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Biddle Law Library - University of Pennsylvania Law School.This item is available to borrow from 1 library branch.
Resource Information
The item Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Biddle Law Library - University of Pennsylvania Law School.
This item is available to borrow from 1 library branch.
- Language
- eng
- Extent
- xxx, 490 pages
- Contents
-
- Allen Riddell
- Style and substance on the US Supreme Court
- Keith Carlson, Daniel N. Rockmore, Allen Riddell, Jon Ashley, and Michael A. Livermore
- Predicting legislative floor action
- Vlad Eidelman, Anastassia Kornilova, and Daniel Argyle
- Writing style and legal traditions
- Jens Frankenreiter
- A computation analysis of California parole suitability hearings
- Analyzing public comments
- Vlad Eidelman, Brian Grom, and Michael A. Livermore
- Introduction: from analogue to digital legal scholarship
- Using text analytics to predict litigation outcomes
- Charlotte S. Alexander, Khalifeh al Jadda, Mohammad Javad Feizollahi, and Anne M. Tucker
- Case vectors: spatial representations of the law using document embeddings
- Elliott Ash and Daniel L. Chen
- Reference networks and civil codes
- Adam B. Badawi and Guiseppe Dari-Mattiacci
- Attorney voice and the US Supreme Court
- Daniel L. Chen, Yosh Halberstam, Manoj Kumar, and Alan C.L. Yu
- Detecting Ideology in judicial language
- Marion Dumas
- Distant reading the law
- Opinion clarity in state and federal trial courts
- Adam Feldman
- Machine learning and the rule of law
- Daniel L. Chen
- The law search turing rest
- Michael A. Livermore and Daniel N. Rockmore
- Michael A. Livermore and Daniel N. Rockmore
- Big data, machine learning, and the credibility revolution in empirical legal studies
- Ryan Copus, Ryan Hubert, and Hannah Laqueur
- Text as observational data
- Marion Dumas and Jens Frankenreiter
- Prediction before inference
- Isbn
- 9781947864085
- Label
- Law as data : computation, text, & the future of legal analysis
- Title
- Law as data
- Title remainder
- computation, text, & the future of legal analysis
- Statement of responsibility
- Michael A. Livermore, Daniel N. Rockmore, editors
- Language
- eng
- Cataloging source
- EVK
- Illustrations
- illustrations
- Index
- no index present
- Literary form
- non fiction
- Nature of contents
- bibliography
- http://library.link/vocab/relatedWorkOrContributorName
-
- Livermore, Michael A.
- Rockmore, Daniel N.
- http://library.link/vocab/subjectName
-
- Technology and law
- Law
- Big data
- Label
- Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors
- Bibliography note
- Includes bibliographical references
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- Allen Riddell
- Style and substance on the US Supreme Court
- Keith Carlson, Daniel N. Rockmore, Allen Riddell, Jon Ashley, and Michael A. Livermore
- Predicting legislative floor action
- Vlad Eidelman, Anastassia Kornilova, and Daniel Argyle
- Writing style and legal traditions
- Jens Frankenreiter
- A computation analysis of California parole suitability hearings
- Analyzing public comments
- Vlad Eidelman, Brian Grom, and Michael A. Livermore
- Introduction: from analogue to digital legal scholarship
- Using text analytics to predict litigation outcomes
- Charlotte S. Alexander, Khalifeh al Jadda, Mohammad Javad Feizollahi, and Anne M. Tucker
- Case vectors: spatial representations of the law using document embeddings
- Elliott Ash and Daniel L. Chen
- Reference networks and civil codes
- Adam B. Badawi and Guiseppe Dari-Mattiacci
- Attorney voice and the US Supreme Court
- Daniel L. Chen, Yosh Halberstam, Manoj Kumar, and Alan C.L. Yu
- Detecting Ideology in judicial language
- Marion Dumas
- Distant reading the law
- Opinion clarity in state and federal trial courts
- Adam Feldman
- Machine learning and the rule of law
- Daniel L. Chen
- The law search turing rest
- Michael A. Livermore and Daniel N. Rockmore
- Michael A. Livermore and Daniel N. Rockmore
- Big data, machine learning, and the credibility revolution in empirical legal studies
- Ryan Copus, Ryan Hubert, and Hannah Laqueur
- Text as observational data
- Marion Dumas and Jens Frankenreiter
- Prediction before inference
- Dimensions
- 26 cm
- Extent
- xxx, 490 pages
- Isbn
- 9781947864085
- Lccn
- 2019941906
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- Other physical details
- illustrations
- System control number
- (OCoLC)1104139256
- Label
- Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors
- Bibliography note
- Includes bibliographical references
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- Allen Riddell
- Style and substance on the US Supreme Court
- Keith Carlson, Daniel N. Rockmore, Allen Riddell, Jon Ashley, and Michael A. Livermore
- Predicting legislative floor action
- Vlad Eidelman, Anastassia Kornilova, and Daniel Argyle
- Writing style and legal traditions
- Jens Frankenreiter
- A computation analysis of California parole suitability hearings
- Analyzing public comments
- Vlad Eidelman, Brian Grom, and Michael A. Livermore
- Introduction: from analogue to digital legal scholarship
- Using text analytics to predict litigation outcomes
- Charlotte S. Alexander, Khalifeh al Jadda, Mohammad Javad Feizollahi, and Anne M. Tucker
- Case vectors: spatial representations of the law using document embeddings
- Elliott Ash and Daniel L. Chen
- Reference networks and civil codes
- Adam B. Badawi and Guiseppe Dari-Mattiacci
- Attorney voice and the US Supreme Court
- Daniel L. Chen, Yosh Halberstam, Manoj Kumar, and Alan C.L. Yu
- Detecting Ideology in judicial language
- Marion Dumas
- Distant reading the law
- Opinion clarity in state and federal trial courts
- Adam Feldman
- Machine learning and the rule of law
- Daniel L. Chen
- The law search turing rest
- Michael A. Livermore and Daniel N. Rockmore
- Michael A. Livermore and Daniel N. Rockmore
- Big data, machine learning, and the credibility revolution in empirical legal studies
- Ryan Copus, Ryan Hubert, and Hannah Laqueur
- Text as observational data
- Marion Dumas and Jens Frankenreiter
- Prediction before inference
- Dimensions
- 26 cm
- Extent
- xxx, 490 pages
- Isbn
- 9781947864085
- Lccn
- 2019941906
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- Other physical details
- illustrations
- System control number
- (OCoLC)1104139256
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.law.upenn.edu/portal/Law-as-data--computation-text--the-future-of/gwEN4NADffo/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.law.upenn.edu/portal/Law-as-data--computation-text--the-future-of/gwEN4NADffo/">Law as data : computation, text, & the future of legal analysis, Michael A. Livermore, Daniel N. Rockmore, editors</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.law.upenn.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.law.upenn.edu/">Biddle Law Library - University of Pennsylvania Law School</a></span></span></span></span></div>
