Conversational Moves in Talking about Body-image in all Female Interactions
Bibliographic record
Abstract
This paper examines the extracts taken from daily conversations as well as from a serial TV play respectively involving female postgraduate students and professional women. The aim of this research is to see whether Guendouzi’s (2004) conversational moves in talking about body-size can be generalized. The extracts are analyzed based on Guendouzi’s model and Brown and Levinson’s (1987) face threat theory. It is found that Guendouzi’s model is only applicable in the circumstance when the speaker exposes herself to face threat. A new model, which fits the situation when the speaker exposes the hearer to face threat, has been tentatively noted based on the analysis of data. Key words: body-image, face threat, politeness, conversational moves Resume: Le present article examine des extraits des conversations quotidiennes ainsi que ceux d’un feuilleton televisuel qui concernent respectivement les etudiantes chercheuses et les femmes professionnelles. Le but de cette etude est de verifier si le mouvement conversationnel de Guendouzi (2004) dans la discussion sur la taille du corps peut etre generalise. Les extraits sont analyses sur la base du modele de Guendouzi et la theorie d’affronter le menace de Brown et Levinson (1987). On trouve que le modele de Guendouzi n’est applicable qu’a la circonstance dans laquelle l’orateur expose lui-meme au menace. Un nouveau modele, qui convient a la situation dans laquelle l’orateur expose l’auditeur au menace, a ete experimentalement marque sur la base de l’analyse des donnees. Mots-Cles: image du corps, affronter le menace, politesse, mouvement conversationnel 摘 要：本文以 Guendouzi在 2004年提出的話步模式和 Levinson在 1987年提出的威脅面子理論位框架對語料進行分析，研究發現 Guendouzi提出的話步只適用於說話人把自己的面子暴露在外的境況，本文根據對語料的分析嘗試性地提出了說話人把聽話人的面子暴露出來的話步。 關鍵詞：身體形象；威脅面子；禮貌；話步
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".