Conceptual Metaphors and Rhetoric in Barack Obama’s and Xi Jinping’s Diplomatic Discourse in Africa and Europe
Bibliographic record
Abstract
This paper examines the use of conceptual metaphors in Barack Obama’s and Xi Jinping’s diplomatic discourse in both Africa and Europe. Drawing on four speeches, this paper begins by examining the pervasiveness of metaphor utility in the speeches by using Pragglejazz Metaphor Identification Procedure. This paper examines the underlying concepts in the identified metaphors by using Lakoff and Johnson conceptual metaphor framework. Finally, this paper examines the significance of conceptual metaphors as a rhetorical strategy in diplomatic discourse. This paper found out that both Barack Obama and Xi Jinping employed an exceptionally high number of metaphors in their discourse in Africa and Europe. We found out that metaphors used by each leader do form an underlying concept. Barack Obama’s diplomatic discourse embodies journey metaphors while Xi Jinping’s diplomatic discourse embodies nature metaphors. The paper illustrates how both leaders draw on neutral lexical units such as distance, crossroads, pace, path, water, lions, mountains, wells, et cetera and charge them with metaphors as a rhetorical strategy in order to draw African and European audiences closer to their primary message.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".