A Discourse Study of Cognitive Frame Construction of ‘China’ in American Economic News
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
This study delves into the complicated yet rewarding examination of the cognitive frame construction and the evoking established frame to interpret China and its economy in American Economic Newspapers. It aims to demystify how linguistic expressions, especially stimuli, influence discourse consumers’ cognition and framing process of a relative object, event and phenomenon in the world. Drawing insights from empirical data in China-related American economic news (CAEN) discourse, the authors adopt Force Dynamics Model (Talmy, 1988, 2000) to illustrate the cognitive frame and its framing process that news discourse constructs. The analyses demonstrate that the employment of Force-dynamic stimuli in CAEN discourse will cause news consumers/readers to conceptualize China as being either a weak and ineffectual power or a ferocious and vicious force. These recurring linguistic stimuli, therefore, construct fixed frames in the mind of the discourse consumers and these frames are used to help them interpret and understand an object, event or a phenomenon in a pejorative light. Consequently, the framed knowledge can be used to manipulate discourse consumers’ conception and behavior. The study enriches the existing body of work on cognitive linguistic analysis to discover the relationship between language and cognition, and interpreting the construction process of cognitive frame.
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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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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