Bibliographic record
Abstract
Abstract Communication of emotion is at the heart of human interaction. For second language (L2) learners, the ability to communicate one’s emotion is crucial, especially in the context of study abroad when they are in frequent contact with native speakers. The aim of the case study is to investigate how an American sojourner Puppies and her Chinese roommate Kiki (both pseudonyms) participated in conversational narratives in the dormitory to construct emotions, and how the contextualized interaction facilitated Puppies’ development of a linguistic repertoire for the expression of emotion in Chinese. Informed by Vygotskian sociocultural theory, the study followed the genetic method in tracing the history of Puppies’ Chinese emotional repertoire across the semester, thereby elucidating the language developmental processes in the situated oral interaction. Audio-recorded everyday interaction in the dorm is triangulated by Puppies’ responses to the pre- and post-Mandarin Awareness Interview and interviews with Puppies and Kiki. Analysis revealed that the contextualized dorm talk provided abundant L2 resources for Puppies to develop a L2 emotional repertoire, especially fear-related emotion expressions. A discrepancy in the product of development as gleaned from the Mandarin Awareness Interview, and the process of development as seen in the naturally occurring dorm talk, suggests that Puppies’ use or non-use of local emotional expressions could be mediated by her partial understanding of the forms and the speech style and identity she wished to assume.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".