Macrostructural Aspects in Oral Narratives in Brazilian Portuguese by Left and Right Hemisphere Stroke Patients With Low Education and Low Socioeconomic Status
Bibliographic record
Abstract
OBJECTIVE: Individuals with a stroke in either the left hemisphere (LH) or the right hemisphere (RH) often present macrostructural impairments in narrative abilities. Understanding the potential influence of low education and low socioeconomic status (SES) is critical to a more effective assessment of poststroke language. The first aim was to investigate macrostructural processing in low-education and low-SES individuals with stroke in the LH or RH or without brain damage. The second aim was to verify the relationships between macrolinguistic, neuropsychological, and sociodemographic variables. METHOD: = 16) chronic ischemic stroke and 16 matched (age, education, and SES) healthy controls produced three oral picture-sequence narratives. The macrostructural aspects analyzed were cohesion, coherence, narrativity, macropropositions, and index of lexical informativeness and were compared among the three groups. Then, exploratory correlations were performed to assess associations between sociodemographic (such as SES), neuropsychological, and macrostructural variables. RESULTS: Both the LH and the RH presented impairments in the local macrostructural aspect (cohesion), whereas the RH also presented impairments in more global aspects (global coherence and macropropositions). All five macrostructural variables correlated with each other, with higher correlations with narrativity. Naming was correlated with all macrostructural variables, as well as prestroke reading and writing habits (RWH), showing that higher naming accuracy and higher RWH are associated with better macrostructural skills. CONCLUSIONS: The present results corroborate the role of the LH in more local processing and that of the RH in more global aspects of discourse. Moreover, this study highlights the importance of investigating discourse processing in healthy and clinical populations of understudied languages such as Brazilian Portuguese, with various levels of education, SES, and RWH.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".