Bibliographic record
Abstract
Abstract Psycholinguistic approaches to examining bilingualism are relatively recent applications that have emerged in the 20th century. The fact that there are more than 7,000 current languages in the world, with the majority of the population actively using more than one language, offers the opportunity to examine language and cognitive processes in a way that is more reflective of human nature. While it was once believed that exposing infants and children to more than one language could lead to negative consequences for cognition and overall language competence, current evidence shows that this is not the case. Among the many topics studied in psycholinguistics and bilingualism is whether two language systems share an integrated network and overlap in the brain, and how the mind deals with cross-linguistic activation and competition from one language when processing in another. Innovative behavioral, electrophysiological, and neuroscientific methods have significantly elucidated our understanding of these issues. The current state of the psychology and neuroscience of bilingualism finds itself at the crossroads of uncovering a holistic view of how multiple languages are processed and represented in the mind and brain. Current issues, such as exploring the cognitive and neurological consequences of bilingualism, are at the forefront of these discussions.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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".