Tense and agreement processing in native Spanish speakers with aphasia
Bibliographic record
Abstract
Abstract Several cross-linguistic studies have reported an impairment of verbal morphosyntax in People with Aphasia (PWA), highlighting a greater impact on tense morphology in contrast to agreement-inflectional morphology ( Benedet, Christiansen & Goodglass, 1998 ; Friedmann & Grodzinsky, 1997 , 2000 ; Gavarrò & Martínez-Ferreiro, 2007 ; Kok et al., 2007 ; Wenzlaff & Clahsen, 2004 ). The Diacritical Encoding and Retrieval Hypothesis (DERH, Faroqi-Shah & Thompson, 2007 ) postulates that this deficit is due to a specific difficulty projecting the semantic time information to the morphosyntax of verbs, related to processing limitations in PWA. This study aimed to assess the processing of the tense and agreement inflection in Spanish-speaking PWA. A group of 9 PWA completed four tasks designed to study verbal inflection production and comprehension in Spanish: Sentence Completion, Sentence Elicitation, Grammaticality Judgements and Sentence-Picture Matching. As expected, PWA showed a significatively greater impairment in tense inflection compared to agreement inflection. Furthermore, the analysis showed that this differential impairment manifested when PWA were asked to encode semantic time information and retrieve the corresponding verb morphology. These findings are consistent with the postulates of the DERH.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".