Analisis Wacana Kritis Teks Berita Kasus Terbongkarnya Perlakuan Istimewa terhadap Terpidana Suap Arthalyta Suryani pada Media Online
Bibliographic record
Abstract
Every choice of meaning is ideologically motivated. Ideology is most effective when its working is least visible. Interpreting ideology in a text can be seen from the choice of vocabulary and its grammatical construction. To analyze it we need to interpret not just the text but also the relationship between text, and its social condition. According to Fairclough, they can be grouped in three steps, those are description, interpretation and explanation. The stage of description is concerned with formal properties of the text, the interpretation is concerned with the relationship between text and its interactions, the explanation is concerned with the relationship between interpretation and social context. This research aims to analysis the coverage about the revealed case of preferential treatment of Arthalyta Suryani, a convicted bribe, at Pondok Bambu detention written by two online media these are detikNews.com and kompas.com by analyzing their appraisal system and their intertextuality. From the data analysis, ideology of the two media about this case can be seen. The data is taken from the news posted on January the tenth to twelfth 2010. The methods used to analyze the data are referential method, substitusional method and abductive inference method. Referential method is to analyze appraisal system and discursivity intertextuality of the text. In order to make the analysis of appraisal system valid, the substitusional method is needed. Then abductive inference method is needed to analyze manifest intertextuality of the text. From the analysis of the data, it can be concluded that every media has its own way to state its ideology. The ideology has closed relation with target market that is the reader. DetikNews.com is strightforward and short news, with incisive vocabulary choices, they are related to news item genre that detikNews.com has, but this media is lack of intertextuality. It makes the news superficial. On the other way, kompas.com has a deep coverage and strong intertextuality, it is suitable for someone who wants comprehensive information.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".