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Using the Semantic Scholar Open Research Corpus (SSORC) of over 175 million scholarly articles, the study measures prevalence in abstracts from 1970–2020 for terms targeting ethnicity, gender, sexual orientation, gender identity, minority religious sentiment, age, body weight, and disability. Relationships between academic usage and corresponding news media prevalence are then assessed, alongside temporal dynamics of additional social-justice-related terms.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/themes-in-academic-literature-prejudice-and-social-justice/588217/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/themes-in-academic-literature-prejudice-and-social-justice/588217.png","ImageObject",300,407,{"name":92,"@type":93},"Aditya","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-01","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What dataset and timeframe are used to study prejudice and social justice terms?","Question",{"text":112,"@type":113},"The analysis uses the Semantic Scholar Open Research Corpus (SSORC) with over 175 million scholarly abstracts. Term prevalence in abstracts is quantified across 1970–2020.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which kinds of prejudice targets are covered in the term prevalence analysis?",{"text":117,"@type":113},"The study quantifies terms denoting prejudice against ethnicity, gender, sexual orientation, gender identity, minority religious sentiment, age, body weight, and disability.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the work connect academic discourse with news media discourse?",{"text":121,"@type":113},"It compares the prevalence dynamics of the same prejudice and social justice terms in academic literature with their prevalence in news media content, including temporal dynamics for additional related terms.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},588217,1792708516,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},962085564549,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Acad. Quest . (2022) 35.2 DOI 10.51845.35.2.5  \nThemes in Academic Literature: Prejudice and Social Justice  \nDavid Rozado  \nIntroduction  \nPrevious scholarly literature has documented a marked increase of words denoting prejudice and social justice themes in news media content.1 This work investigates the prevalence dynamics of such terms in academic papers published in all fields of knowledge. We use the Semantic Scholar Open Research Corpus (SSORC) containing, as of 2020, over 175 million published scholarly articles and associated metadata.2 We quantify the prevalence of words denoting prejudice against ethnicity, gender, sexual orientation, gender identity, minority religious sentiment, age, body weight and disability in SSORC abstracts over the period 1970-2020. We then examine the relationship between the prevalence of such terms in the academic literature and their concomitant prevalence in news media content. Finally, we also analyze the temporal dynamics of an additional set of terms associated with social justice discourse in both the scholarly literature and in news media content. Taken together, these analyses allow us to illuminate the chronological dynamics of prejudice and social justice themes in academic discourse as well as their relationship with news media content.  \nPrevious work published in this journal documented an abrupt increase in the prevalence of prejudice-denoting terms in the New York Times. A follow-up analysis confirmed the trend across forty-seven news media outlets.3 Critically,  \n1 David Rozado,“Prejudice and Victimization Themes in New York Times \" Discourse: A Chronological Analysis,” Academic Questions 33, no. 1 (March 1, 2020): 89–100; David Rozado, Musa Al-Gharbi, Jamin Halberstadt,“Prevalence of Prejudice-Denoting Words in News Media Discourse: A Chronological Analysis,” Social Science Computer Review, July 27, 2021, 08944393211031452, [https://doi](https://doi). org/10.1177/08944393211031452 .  \n2 Waleed Ammar et al.,“Construction of the Literature Graph in Semantic Scholar,” in NAACL, 2018, [https://doi.org/10.18653/v1/N18-3011](https://doi.org/10.18653/v1/N18-3011); John Lee, Ying Cheuk Hui, and Yin Hei Kong,“Semantic Scholar Open Research Corpus,” Digital Scholarship in the Humanities, April 2016, [https://academic.oup.com/](https://academic.oup.com/)[ ](https://academic.oup.com/)[dsh/article-lookup/doi/10.1093/llc/fqu052.](dsh/article-lookup/doi/10.1093/llc/fqu052.)  \n3 Rozado,“Prejudice and Victimization Themes in New York Times Discourse”; Rozado, Al-Gharbi, and Halberstadt,“Prevalence of Prejudice-Denoting Words in News Media Discourse.”  \nDavid Rozado holds a Ph. D. in Computer Science from the Autonomous University of Madrid and is a widely published author in that field. Prof. Rozado has been teaching at New Zealand’s Otago Polytechnic since 2015; [david. rozado@op.ac. nz. His](david. rozado@op.ac. nz. His) research interests are computational content analysis and accessibility software. Rozado last appeared in these pages with “Prejudice and Victimization Themes in New York Times Discourse: A Chronological Analysis,” in Spring 2020.  \nthat paper also revealed that the rising trend preceded the 2015 emergence of Donald Trump on the U. S. political scene. In general, the abrupt increase started within the 2010-2014 time frame and remained at historical highs through at least the first five months of the Biden Administration starting in January 2021.4  \nOver the same temporal period (2010-2019), public opinion surveys show increasing public concern in the U. S. about prejudice, particularly among voters of the Democratic Party.5 Paradoxically, other longitudinal public opinion surveys have reported a decrease in overt prejudicial attitudes in U. S. society since the 1970s.6 Consequently, the role of news media discourse in shaping public concern about prejudice, as predicted by agenda-setting theory,7 has been investigated.8 Similarly, characterizing the prevalence of prejud","cbCaiePN0GuE8ZVG","https://ap.wps.com/l/cbCaiePN0GuE8ZVG","pdf",799876,14,"English","# Introduction\n# Methods","[{\"question\":\"What dataset and timeframe are used to study prejudice and social justice terms?\",\"answer\":\"The analysis uses the Semantic Scholar Open Research Corpus (SSORC) with over 175 million scholarly abstracts. Term prevalence in abstracts is quantified across 1970–2020.\"},{\"question\":\"Which kinds of prejudice targets are covered in the term prevalence analysis?\",\"answer\":\"The study quantifies terms denoting prejudice against ethnicity, gender, sexual orientation, gender identity, minority religious sentiment, age, body weight, and disability.\"},{\"question\":\"How does the work connect academic discourse with news media discourse?\",\"answer\":\"It compares the prevalence dynamics of the same prejudice and social justice terms in academic literature with their prevalence in news media content, including temporal dynamics for additional related terms.\"}]","Themes in Academic Literature - Prejudice and Social Justice | PDF",1792064771,35]