The embodiment of emotional words in a second language: An eye-movement study
Bibliographic record
Abstract
The hypothesis that word representations are emotionally impoverished in a second language (L2) has variable support. However, this hypothesis has only been tested using tasks that present words in isolation or that require laboratory-specific decisions. Here, we recorded eye movements for 34 bilinguals who read sentences in their L2 with no goal other than comprehension, and compared them to 43 first language readers taken from our prior study. Positive words were read more quickly than neutral words in the L2 across first-pass reading time measures. However, this emotional advantage was absent for negative words for the earliest measures. Moreover, negative words but not positive words were influenced by concreteness, frequency and L2 proficiency in a manner similar to neutral words. Taken together, the findings suggest that only negative words are at risk of emotional disembodiment during L2 reading, perhaps because a positivity bias in L2 experiences ensures that positive words are emotionally grounded.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".