Examining Bilingual Language Control Using the Stroop Task
Bibliographic record
Abstract
The Stroop task in its many variations has been used in fields such as psychology, linguistics, and neuroscience to examine questions regarding the automaticity of reading, language processing, and cognitive control, among others. When looking at bilingual individuals, this task can be used to obtain measures of language interference and control in both a bilingual's first language (L1) and second language (L2), as well as for testing the bilingual advantage hypothesis. The Stroop task presents participants with color terms written in congruent colors (e.g., the word RED written in red font), incongruent colors (e.g., the word RED written in green font), in addition to noncolor terms for control (e.g., the word TREE presented in any color), and uses the reaction times from the different conditions to assess the degree of interference and facilitation. In the covert version of the Stroop bilingual task (i.e., participants respond by pressing a button rather than naming aloud), stimuli in the L1 and the L2 are typically presented in separate blocks. While this allows for a simple, yet effective assessment of processing and cognitive control in each language, it fails to capture any potential differences in processing and control within bilingual young adult groups. The present task combines single-language blocks with a novel mixed-language block to increase the level of difficulty of the task, thus making it suitable for testing cognitive control in young adults. Representative results showing differences between performance in the single-language vs. mixed-language blocks are presented, and the benefits of a mixed-language block are discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".