A pragmatic study of the speech acts of praise and compliment in selected public statements of Justin Trudeau دراسة تداولية لأفعال المدح والمجاملة في تصريحات مختارة لجاستن ترودو
Bibliographic record
Abstract
This paper aims to investigate a corpus of sixty posts and tweets which include speech acts of praise and compliment by Justin Trudeau, the current Canadian prime minister since 2015. This type of speech acts falls into the “expressives” category in Searle’s taxonomy of speech acts. Moreover, the methodology which will be adopted in this research is the pragmatic approach and the speech act of praise model will be used to analyse the data in this study. This model is developed mainly from Kampf and Danziger’s (2018) analytical framework which they used to analyse the different speech acts of praise delivered by selected politicians. Moreover, since their analytical framework did not include the speech act of self-praise, I had to adopt Rudiger’s and Dayter’s (2020) taxonomy of the speech act of self-praise and include it in my model. In addition to this, I studied the frequency of occurrence of the different linguistic devices used by Trudeau to deliver the speech acts of praise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".