Uniting for Peace: A Speech Act Analysis of the United Nations General Assembly Resolution 377 A (V)
Bibliographic record
Abstract
This study examines the use of speech acts in the United Nations General Assembly Resolution number 377 A (V). Using Bach’s (2003) speech acts categorizations, the study aims to identify the illocutionary and perlocutionary acts used in the resolution as it aims to examine how the resolution is constructed and interpreted. The study reveals that the resolution incorporates instances of directive, constative and commissive illocutionary acts. The perlocutionary effects of the directive illocutionary acts comprise instructing, advising, urging, requesting and recommending; the perlocutionary effects of the constative illocutionary acts include reaffirming, recognizing, and stating; and the perlocutionary effects of the commissive illocutionary acts encompass assuring and inviting. It is also found that the resolution is constructed using two structural patterns: the constative-directive pattern to recognize accountability then provide regulative directives (herewith, it shall be that) and the commissive-constative-directive pattern to renew commitment, recognize responsibilities and provide regulative directives. The study furthermore reveals that the resolution encompasses high degree of imposition in the regulatory directive illocutionary acts, but the level of imposition varied when addressing entities. The resolution comprises high degree of imposition in addressing the General Assembly, the Secretary General and committees but low (weakened) degree of imposition in addressing the Security Council, which reflects different power relations in 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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".