Mental Imagery and Affect in English/French Bilingual Readers: A Cross-Linguistic Perspective
Bibliographic record
Abstract
Abstract: We investigated the evocation of mental imagery and affect in English/French bilinguals to determine whether the linguistic demands of reading in a second language (L2) limit readers’ ability to form non-verbal text representations of literary stories. The participants were 26 Grade 11 French immersion students enrolled in a Canadian high school. Each student read two literary stories, one in English and another in French. Next they rated story paragraphs for the degree of either mental imagery or emotional response evoked. Later, students reread the same texts and completed a writing task in which they reported their imagery or emotions in response to the two highest-rated paragraphs. Moderate to high correlations were found between ratings of imagery and emotional response for each story, for two French stories combined, for two English stories combined, and for all stories in both languages combined. Reading times were somewhat longer for the French versions. The patterns of response for both the ratings and the written reports replicate and extend earlier research and suggest that as bilingual readers progress in their ability to read in their L2, reports of imagery and affect become closer in kind and number to those reported in response to reading the same text in their first language.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".