A Research on Cognitive Metonymy Models of News Headlines from ft.com
Bibliographic record
Abstract
News as a literary form adopted by public media, has been playing an important role in reporting international events. Due to the fast pace of life in today’s society, readers usually grasp the major events by just reading the headlines. While the headline as the “eye” of a piece of news, enables the readers to catch the key and hot point at the first time by means of its terse and concise words. With the rise of cognitive linguistics, metonymy is regarded not only as a rhetorical device, but also as a way of thinking the objective world. What’s more, metonymy also plays an important role in the news headline discourse organization. Therefore, based on the cognitive metonymy theory, this research makes the case studies of the news headlines which contain metonymy in order to answer the two questions: (1) Among the different kinds of cognitive metonymy models, which one is used the most frequently in news headlines? (2) Are the natures and values of news headlines related to the choice of these cognitive metonymy models?
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 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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".