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  5. Systems in Language: Text Analysis of Government Reports of the Irish Industrial School System with Word Embedding
 
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Systems in Language: Text Analysis of Government Reports of the Irish Industrial School System with Word Embedding

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Author(s)
Keane, Mark T. 
Pine, Emilie 
Leavy, Susan 
Uri
http://hdl.handle.net/10197/10884
Date Issued
03 June 2019
Date Available
11T10:49:14Z July 2019
Abstract
Industrial Memories is a digital humanities initiative to supplement close readings of a government report with new distant readings, using text analytics techniques. The Ryan Report (2009), the official report of the Commission to Inquire into Child Abuse (CICA), details the systematic abuse of thousands of children 15 from 1936 to 1999 in residential institutions run by religious orders and funded and overseen by the Irish State. Arguably, the sheer size of the Ryan Report—over 1 million words— warrants a new approach that blends close readings to witness its findings, with distant readings that help surface system-wide findings embedded in the Report. Although CICA has been lauded internationally for 20 its work, many have critiqued the narrative form of the Ryan Report, for obfuscating key findings and providing poor systemic, statistical summaries that are crucial to evaluating the political and cultural context in which the abuse took place (Keenan, 2013, Child Sexual Abuse and the Catholic Church: Gender, Power, and Organizational Culture. Oxford University Press). In this article, we concentrate on describing the distant reading methodology we adopted, using machine learning and text-analytic methods and report on what they surfaced from the 2 Report. The contribution of this work is threefold: (i) it shows how text analytics can be used to surface new patterns, summaries and results that were not apparent via close reading, (ii) it demonstrates how machine learning can be used to annotate text by using word embedding to compile domain-specific semantic lexicons for feature extraction and (iii) it demonstrates how digital humanities methods can be applied to an official state inquiry with social justice impact.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Journal Article
Publisher
Oxford University Press
Journal
Digital Scholarship in the Humanities
Volume
34
Issue
1
Start Page
i110
End Page
i122
Copyright (Published Version)
2019 the Authors
Keywords
  • Digital humanities

  • Text analytics

  • Ryan Report

  • Child Sexual Abuse

  • Machine learning

  • Social justice

DOI
10.1093/llc/fqz012
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
Scopus© citations
0
Acquisition Date
Feb 6, 2023
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Views
883
Acquisition Date
Feb 6, 2023
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Downloads
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Acquisition Date
Feb 6, 2023
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