Coverart for item
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

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
Contributor
Editor
Subject
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
Instantiates
Publication
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
Publication
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

Library Locations

    • Biddle Law LibraryBorrow it
      3400 Chestnut Street, Philadelphia, Pennsylvania, 19104, US
      39.954941 -75.193362
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