IMPERATIVE SENTENCES IN AMERICAN SERIAL TV GREY’S ANATOMY SEASON 17
Bibliographic record
Abstract
This study focused on analyzing the imperative sentences types and how does it affect the interlocutor that found in the American serial tv Grey’s Anatomy episode 1 of season 17, namely All Tomorrow’s Parties. The researcher uses documentation as data. Meanwhile for the research design, the researcher uses document analysis. For the result of this study, there are three parts of imperative sentence in Grey's Anatomy episode 1 of season 17. They are imperative as command form, imperative as request form, and imperative as suggestion form. Each type of imperative sentence has 2 patterns, namely positive pattern and negative pattern. For imperative as request form, the researcher cannot find any negative pattern. After calculating all the data, the researcher found that imperative as command form is the dominant type of imperative sentences in Grey’s Anatomy. 57,5% of the dialogue appear as command. Meanwhile 17,5% of the dialogue appear as request. It is the least used type of imperative sentences in Grey’s Anatomy episode 1 of season 17. And 25% of the dialogue appear as suggestion. At least a quarter of the dialogue are the imperative as suggestion form.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".