Dressing and Being: Appraising Costume and Identity in English Second-Language Drama
Bibliographic record
Abstract
In many cultures, L2 students are reticent to engage in spontaneous oral L2 production. In Chinese culture, social norms tend to place value on accuracy, which tends to inhibit learners from authentic oral use of the target language. The purpose of this study was to consider the impact of costume, as used in L2 drama, on L2 selves, and attitudes towards specific elements of authentic language use. Costume has long been understood as eliciting imagination, and permitting the expression of possible and desired selves. Fashion ensembles of many kinds are experienced as having a semiotic “sparkle”, which wearers connect to their own self, as they imagine and perform possible selves. In this study, 78 second-language actors were asked to write a brief commentary on how they responded to their costume. This qualitative data was analysed using Appraisal analysis, indicating a majority of positive evaluations. It was also analysed using possible self theory. Comments also showed that L2 actors felt that costumes impacted their emotions and imagination of self, which improved their second language use, cultural performance. They felt costume integrated their oral production with their choices of social register, and their paralinguistic and kinetic performance.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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 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".