2008,Vol.4,No.1,1-7 Canadian Academy of Oriental and Occidental Culture 1 A Study of the Verbal Conflict between Mother and Daughter-in-law in Desperate Housewives
Bibliographic record
Abstract
Abstract: Ting-Toomey proposed face-negotiation theory in the 1980s. For years, face-negotiation theory has been used to explain conflict in communication and cultural differences related to communication. As we know, conflict is a very natural phenomenon in the conversation of different cultures. However, people have different ways to solve the conflict. This paper studies the conflict between mother and daughter-in-law in TV series. The extracts come from the American TV series Desperate Housewives. The paper aims to answer the two research questions: (1) does the conflict style between family members like mother and daughter-in-law in American TV series Desperate Housewives is also dominating? (2) If it is, how the conversation proceeds under the dominating style? After analyzing the materials, we find that the conflict style between mother and daughter-in-law in American TV series Desperate Housewives is dominating. In addition, although the conflict style between mother and daughter-in-law in American TV series Desperate Housewives is dominating, people also emphasize on the social harmony among family members. Key words: conflict, face-negation theory, mother and daughter-in-law Résumé: Ting-Toomey propose la théorie de la négation de face dans les années 1980. Depuis des années, la théorie de la négociation de face a été utilisée pour expliquer les conflits dans la
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".