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Hits 1 – 16 of 16

1
Emotion and Reason in Political Language ...
Gennaro, Gloria; Ash, Elliott. - : ETH Zurich, 2022
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2
Emotion and Reason in Political Language
In: The Economic Journal, 132 (643) (2022)
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3
Dimensions of Mind in Semantic Space ...
Ash, Elliott; Stammbach, Dominik; Tobia, Kevin. - : ETH Zurich, 2021
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4
Text Semantics Capture Political and Economic Narratives ...
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5
Text Semantics Capture Political and Economic Narratives
In: Center for Law & Economics Working Paper Series, 2021 (11) (2021)
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6
Dimensions of Mind in Semantic Space
In: Center for Law & Economics Working Paper Series, 2021 (14) (2021)
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7
Machine Extraction of Tax Laws from Legislative Texts
In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
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8
Automated fact-value distinction in court opinions
In: ISSN: 0929-1261 ; EISSN: 1572-9990 ; European Journal of Law and Economics ; https://hal.archives-ouvertes.fr/hal-03174376 ; European Journal of Law and Economics, Springer Verlag, 2020, 50 (3), pp.451-467. ⟨10.1007/s10657-020-09645-7⟩ (2020)
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9
Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements ...
Ash, Elliott; Jacobs, Jeff; MacLeod, Bentley. - : ETH Zurich, 2020
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10
More Laws, More Growth? Evidence from U.S. States ...
Ash, Elliott; Morelli, Massimo; Vannoni, Matia. - : ETH Zurich, 2020
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11
Automated fact-value distinction in court opinions ...
Cao, Yu; Ash, Elliott; Chen, Daniel L.. - : ETH Zurich, 2020
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12
Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements
In: 2020 International Conference on Data Mining Workshops (ICDMW) (2020)
Abstract: This paper describes an unsupervised legal document parser which performs a decomposition of labor union contracts into discrete assignments of rights and duties among agents of interest. We use insights from deontic logic applied to modal categories and other linguistic patterns to generate topic-specific measures of relative legal authority. We illustrate the consistency and efficiency of the pipeline by applying it to a large corpus of 35K contracts and validating the resulting outputs. © 2020 IEEE
Keyword: Information Mining; Legal Corpus Analysis; Unsupervised Extraction
URL: https://hdl.handle.net/20.500.11850/473199
https://doi.org/10.3929/ethz-b-000453825
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13
More Laws, More Growth? Evidence from U.S. States
In: Center for Law & Economics Working Paper Series, 15/2020 (2020)
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14
Automated fact-value distinction in court opinions
In: European Journal of Law and Economics, 50 (3) (2020)
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15
Stereotypes in High-Stakes Decisions : Evidence from U.S. Circuit Courts
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16
Stereotypes in High-Stakes Decisions : Evidence from U.S. Circuit Courts
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