Revisiting the Role of Philosophy in Diplomacy and International Relations
Bibliographic record
Abstract
Amid the biased perception that philosophy (unlike science and technology, which are viewed favorably as practical) is far from practice and lacks the ability and aptitude to provide practical solutions to challenges facing human development in modern-day African societies, this chapter seeks to achieve three objectives: first, to debunk the notion that philosophy has no value in practical areas such as diplomacy and international relations (IR) using personal and empirical evidence; second, to provide pragmatic expositions to highlight philosophy's significant value and contribution in the fields of diplomacy and IR; and third, to demonstrate an interface between philosophy, diplomacy, and IR. This chapter's main argument is that “much of what is learned in philosophy can be applied virtually in any endeavor, because philosophy touches so many subjects including the noble profession of diplomacy.” For a diplomat to master the art of diplomatic craft specifically, he/she ought to possess an enduring ability to understand the interface between theory and practice, which philosophy provides. The fulcrum of a diplomat's ability to understand the connection between theory and practice lies in their aptitude to comprehend the performative act of philosophy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".