Task effects in Farsi-English bilinguals’ use of gestures
Bibliographic record
Abstract
Abstract The primary purpose of this study was to test whether there were task differences (storytelling vs. language learning history) in gesture frequency among Farsi-English bilinguals. Given the importance of visuospatial processing for representational gestures, we predicted that participants would produce more representational gestures when telling a story than when recounting their language learning history (i.e., how they learned English as second language), and no task differences in beat production. A secondary purpose of this study was to test if there were differences in gesture production by language. We predicted that the participants would use more representational and beat gestures in their second language (English) than in Farsi. As predicted, the participants used more representational gestures in story-telling than when talking about their language history in both languages and more beats when speaking English than Farsi. Surprisingly, they used equivalent rates of representational gestures in both languages. We discuss these results in terms of the different functions of representational gestures and beat gestures.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".