The visual world paradigm for indexing phonological and semantic lexical co-activation in children: A methodological overview
Bibliographic record
Abstract
The visual world paradigm (VWP) can be used to understand the time-course of activation of words and their competitors during spoken word recognition. A target word is presented auditorily (e.g., ‘candy’) while the target word and its competitors are presented visually. Competitors are words that may be activated briefly despite not being the target word. They can sound similar (e.g., ‘candle’), have related meaning (e.g., ‘pie’), or be related in some other way to a presented word (e.g., perceptually related such as a ‘rope’ and ‘snake’). The visual world paradigm allows the researcher to examine what words, from a fixed set of images on the screen, the participant is considering. This is time locked in milliseconds, typically starting from the target word presentation and before the participant has fully recognized the target word. There are many linguistic applications and variations to the task. In our manuscript, we describe a 4-image version of the VWP for use in a study with French-speaking children between ages 3-7 years old. Our task allows for the examination of both phonological and semantic co-activation of auditorily presented words. Children complete 36 test trials during the experiment. During a test trial, a set of 4 images are presented equidistant from the center of the screen. One image is the ‘target’ and the other three images are either competitors (phonologically or semantically related) or unrelated to the target. Children hear the label of the target image. In our version, children are also instructed to point at the corresponding image to establish word choice. Children’s looks to the images are indexed during the first 2000 ms after the onset of the auditory word. Analyses examine children’s looks, not just to the labeled target image, but also to the competitors. This gives researchers insight into the activation and inhibition of presented and competing words during the time-course of spoken word recognition.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".