The dynamic nature of assimilation and accommodation procedures in the brains of <scp>C</scp>hinese–<scp>E</scp>nglish and <scp>E</scp>nglish–<scp>C</scp>hinese bilinguals
Bibliographic record
Abstract
The framework of assimilation and accommodation has been proposed to explain the brain mechanisms supporting second language reading acquisition (Perfetti et al. [2007]: Bilingual Lang Cogn 10:131). Assimilation refers to using the procedures of the native language network in the acquisition of a new writing system, whereas accommodation refers to using second language procedures for reading the newly acquired writing system. We investigated assimilation and accommodation patterns in the brains of bilingual individuals by recruiting a group of Chinese-English bilinguals and a group of English-Chinese bilinguals to perform lexical decision tasks in both English and Chinese. The key question was whether the assimilation/accommodation procedures supporting second language reading in the brains of Chinese-English and English-Chinese bilinguals were dynamic, i.e., modulated by proficiency in the second language and perceptual features of the second language's script. Perceptual features of the scripts were manipulated through orthographic degradation by inserting spaces between the radicals of a Chinese character or between the syllables of an English word. This manipulation disrupts the visual configuration of the orthography but does not change its more fundamental design principles. We found that for English-Chinese bilinguals, higher proficiency was associated with greater accommodation, suggesting that the accommodation procedure in a bilingual individual's brain is modulated by second language proficiency. Most interestingly, we found that the assimilation/accommodation effects vanished or diminished when orthographically degraded scripts were processed by both Chinese-English and English-Chinese bilinguals, suggesting that the assimilation/accommodation procedures in a bilingual individual's brain are modulated by perceptual features of orthography. This work therefore offers a new, dynamic perspective for our understanding of the assimilation/accommodation framework for second language acquisition.
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 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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".