Metaphor-Based Analysis of Joe Biden’s and George Washington’s Inaugural Speeches
Bibliographic record
Abstract
This paper analyzes how conceptual metaphor is used as a persuasive tool in Joseph Biden’s and George Washington’s inaugural speeches. The speeches are analyzed using Conceptual Metaphor Theory. A source-based approach to metaphor analysis is adopted in this paper. Statistical findings are used to examine how metaphor is utilized to frame certain political topics. The study demonstrates that metaphor is a vital persuasive tool in political discourse. The use of conceptual metaphors persuades and appeals to people’s emotions. The paper shows that Biden utilized more conceptual metaphors than Washington. This indicates the need and importance Biden attaches to persuasive rhetoric of which the use of metaphor successfully provides and attains. The nature of conceptual metaphor in both speeches reveals the existence of diachronic differences in how metaphors were used. This metaphor variation which reflects changes in society is ascribed to the differences in ideologies and the zeitgeist of the two eras in which the speeches took place.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".