Quotation as a Key to the Investigation of Ideological Manipulation in News Trans-Editing in the Taiwanese Press1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
News trans-editing, which has gate-keeping and adaptation as distinctive features, is widely adopted by news organizations to produce suitable target texts. Since news organizations are socially, politically and economically situated, news trans-editing is always mediated in one way or another. Using the trans-editing of quotation as a key, this paper conducts an empirical case study and investigates how the target newspapers’ ideologies systematically manipulate the seemingly “objective” trans-edited news texts. The case study data covers some news texts concerning China’s anti-secession law from the New York Times and the Washington Post , and their trans-edited Chinese versions from the China Times , the United Daily News and the Liberty Times in Taiwan. After introducing the relevant contextual factors, a comparative study of the source and target texts is made in terms of the following four aspects of quotation to identify recurrent shifts: quotation modes, news sources, quotation contents and reporting verbs. By analyzing ideological reasons behind the recurrent shifts against the contextual factors, this paper elaborates on the target newspapers’ ideological manipulation with practical examples.
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.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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