Critical Discourse Analysis of Micro and Macro Structures in Talks by Two Iranian Presidents at the United Nations General Assembly: A Socio-cognitive Perspective
Bibliographic record
Abstract
This study analyzes official public talks by two Iranian presidents—Hassan Rouhani and Mahmoud Ahmadinejad—within the framework of Critical Discourse Studies (CDS). The study focuses on discoursal features in addresses of these presidents to the United Nations General Assembly at the micro-level (25 discursive devices) and the macro-level (positive self-representation and negative other-representation). The investigation attempts to determine whether significant differences existing in the micro and macro structures of these political discourses may be reflective of such factors as dissimilarities in political stance, world view and personal background. Combining quantitative and qualitative elements of analysis, the study demonstrates that consensus, illustration, hyperbole and polarization were used more frequently, whereas lexicalization and vagueness less frequently by Rouhani than by Ahmadinejad. At the semantic macro-level, Rouhani employed more positive self-representations and Ahmadinejad relied stronger on negative other-representation. Results are interpreted within the CDS framework of political discourse.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".