Exploring Religious Discourse Authority among Nobel Peace Prize Laureates: A Pragmatic Approach
Bibliographic record
Abstract
Authority is the influence of a rhetorical nature that the discourse possesses from the authority of the addressee's position and the nature of the relationships that arise between him or her and the addressees. This paper aims to explore the role of the authority of the religious discourse among Nobel Peace Prize laureates from a pragmatic perspective. The methodology involves using the pragmatic approach relating to linguistic argumentation as it was revealed to Chaim Perelman. The methodology is also a qualitative methodology concerned with understanding the phenomenon within its context and uses inference and exploration, benefiting from a set of inputs related to the phenomenon without resorting to precise statistics to infer the phenomenon. The study sample includes speeches collected in the book Nobel Peace Prize Laureates Speeches. The findings demonstrate that various Nobel Peace Prize laureates have resorted to the authority of religious discourse to support their speeches with pieces of evidence gleaned from the religious discourses. The results also show that the most common authority of the holy discourse in the various religions in the speeches of Nobel laureates was the authority of the holy books, i.e. the Torah, the Bible, and the Holy Qur’an. That said, this study recommends studying the speeches of Nobel Peace Prize winners from the perspective of cultural sustainability.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".