SSP Forum: Fernanda Kramer and Penny Pan (M.S. Candidates)
The
Symbolic Systems Forum
presents
Philanthropy and News Coverage: Measuring Funder Influence on Journalism
Fernanda Kramer (M.S. Candidate)
Symbolic Systems Program
and
Towards a Computational Account of Projection Inferences
Penny Pan (M.S. Candidate)
Symbolic Systems Program
Tuesday, May 16, 2023
4:30-5:20 pm
Margaret Jacks Hall (Bldg. 460), Room 126
ABSTRACTS:
(1) Fernanda Kramer, "Philanthropy and News Coverage: Measuring Funder Influence on Journalism" (primary advisor: Todd Davies, Symbolic Systems)
The financial pressures brought on by the rise of digital news consumption and the aftermath of the 2008 financial crisis have led journalistic organizations to seek funding from philanthropic foundations. As a result, questions have been raised about the potential influence these foundations have on news content. This study investigates the influence of philanthropy on journalism via a mixed-methods case study of the Bill and Melinda Gates Foundation. We are analyzing the influence of the Gates Foundation on news coverage of Bill Gates, the Gates Foundation, and organizations and issues related to Covid-19 vaccine development, licensing, and distribution globally -- for which the Gates Foundation has provided substantial funding and has exerted influence on policy decisions. This project builds on an earlier project which focused on defining journalism in the digital age and developing criteria to identify journalistic organizations, non-promotional news republishers, and promotional news organizations.
(2) Penny Pan, "Towards a Computational Account of Projection Inferences" (primary advisor: Judith Degen, Linguistics)
Projection inferences are inferences about speaker commitment to a content embedded under an entailment-canceling operator, such as polar interrogatives with clause-embedding predicates (e.g., Does John know that Julian dances salsa?). Inferred speaker belief regarding the embedded content (e.g., whether Julian dances salsa) is modulated by multiple factors, including the predicate used, interlocutors’ prior beliefs about the content, and the content’s at-issueness. In this talk, we will present the empirical results from a behavioral study and propose a probabilistic model as the first step towards a unified computational account of projection inferences about the content embedded under clause-embedding predicates. Overall, the predictions of the model mirror some, but not all, of the empirical patterns, and we will discuss the implication of the results.
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