Bibliographic record
Abstract
Inaugural address in an important part of inauguration ceremony and every new president conceives the speech as an opportunity to promote his policies in order to appealing for people’s support. A common ground is that all presidents are fully prepared for the inaugural address and every speech has become a classic work. Donald Trump, as the new president of America, are facing changes coming from the international environment, the class consolidation, the economic downturn, and the intensification of contradictions. His inaugural address is full of his personal temperament. Although numerous researchers such as Wang Zuoliang, Ding Wangdao and Xu Zhenzhong have analyzed the stylistic features of many public speakers from varied perspectives. But there are few analyses about Trump’s speech style. And the author intends to analyze the style of his address from the aspects of phonetic feature, vocabulary feature, rhetorical feature and syntax feature. According to the author’s findings, Donald Trump raised their people’s awareness of the status quo and patriotism with the help of his unique style of speech. This paper can help us better understand the stylistic feature of speech and the connotations of Trump’s inaugural address.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".