Tom Clancy ś Debt of Honor
Uncanny Ability to Predict The Future
Bibliographic Data
| ID | 22217243 |
|---|---|
| Authors | Abeer Jasim Mohmmed (University of Tikrit), Intisar Rashid Khaleel (University of Tikrit) |
| Year | 2024 |
| Volume | 8 |
| Issue | 9 |
| Pages | 290-304 |
| Publication date | 2024-09-30 |
| Open Access | No |
| Type | ARTICLE |
| Venue | JOURNAL OF LANGUAGE STUDIES (JOURNAL) |
| Journal identifiers | ISSN: 2616-6224 • E-ISSN: 2663-9033 |
| Publisher | Tikrit University (PUBLISHER • IQ) |
| DOI | 10.25130/lang.8.9.19 |
| OpenAlex | W4403035112 |
| Language | EN |
| References cited | 18 |
This paper investigates Tom Clancy's Debt of Honor through the framework of Nicholas Rescher's theory of predication. This philosophical approach examines how language connects concepts with the objects they describe. As Rescher posits, prediction is a crucial mechanism for understanding and organizing our perceptions of the world, enabling effective communication by linking abstract ideas to concrete entities. The objective of this study is to demystify Rescher's theory, presenting it clearly and understandably while highlighting its importance in both theoretical discussions and practical applications. The research begins by outlining the fundamental tenets of Rescher's theory, including how predication operates within everyday language and thought processes. It then applies these principles to the narrative and thematic structures within Debt of Honor, illustrating how the novel's depiction of complex socio-political scenarios can be better understood through the lens of prediction. The study explores the broader implications of Rescher's theory. The paper argues that a deeper understanding of predication can enhance clarity and precision in both philosophical discourse and real-world communication
Debt · Economics · Honor · Internet privacy · Psychoanalysis · Uncanny · Complex Systems and Time Series Analysis · Computer Science · Innovation Diffusion and Forecasting · Psychology · Sports Analytics and Performance · Finance
| Highly cited | No |
|---|