Modality in the Text of Jokowi’s Speech in the Context of the Anniversary of Political Parties in Indonesia: Systemic Functional Linguistics Study
Why this work is in the frame
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Bibliographic record
Abstract
A person's views or opinions can be known from the use of modalities when giving speeches. This study aims to determine and describe the use of modalities in the text of Jokowi's speech in the framework of the Anniversary of Political Parties in Indonesia. This research is a qualitative descriptive research. The data of this study are clauses that have modalities in the text of Jokowi's speech. The technique of collecting data was done by online participatory observation and the technique of analyzing data was done by using interactive data analysis including: data collection, data reduction, data display and conclusion. Meanwhile, the source data of this research from five speeches of Jokowi at the political parties’ anniversary namely: Golkar, Perindo, PDI-Perjuangan, PSI, and Gerindra. The five speeches of Jokowi were downloaded from youtube. The results of this study show that the five speeches of Jokowi used modalization modality and modulation modality with different frequency occurences. Modalization modality dominates in its use with frequency 68 times meanwhile the frequency of modulation modality occurred in 53 times. This research also found 18 markers of modality used by Jokowi in his speech. From 18 markers of modality, it was found 3 markers of modality that were dominant in use, namely: ‘will’, ‘must’, and ‘want’. Thus, it was concluded that Jokowi in his speech had high hopes for the five political parties to bring Indonesia to become a developed country.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it