Bibliographic record
Abstract
This paper explores the role of emotions and corporeal sensations in the experiences of foreign language learning and identity of one Canadian adult learner of Portuguese.Emotions in second and foreign language learning have become the subject of growing interest since other perspectives other than the cognitive have been included in Second Language Acquisition (SLA) research.Yet, much of the recent literature on the relationship of emotions, foreign language learning, and identity continues to reflect the experiences of English language learners, and has also paid little attention to whether learners develop and include an awareness of and an attention to the contribution of corporeal sensations to their experiences of foreign language learning, and identity enactment in the foreign language.This paper draws on concepts of sociocultural theory and construals-of-the-self to understand the learner's perceptions of her experiences learning Portuguese, and of her identity-related experiences in this language with a focus on emotions.Findings suggest that the learner's conceptualisations of her target identity were imagined and constructed also through corporeal sensations that she experienced and regarded as being characteristic of her target language identities.In addition, a connection between past subjective experiences and the learner's perceptions of foreign language identities was also found.With this understanding, this paper calls for future research to expand on this attention to these emotional aspects that, in addition to linguistic ones, may constitute learners' aspirations and ideas of target language identities.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".