Verbal and Behavioural Patterns during Haptic Exploration in Blind and Visual Impaired Children, Implications for Developmental Plasticity
Bibliographic record
Abstract
RESEARCH QUESTION: We investigated whether congenitally totally blind children verbalize during a raised-line identification-task (haptic picture naming task) and whether speech production by congenitally totally blind (CTB) children differs as compared to that by sighted but partially visually impaired (SVI) children. METHOD: Our experimental design consisted of two exploration-identification tasks separated by a drawing task. During each phase of the experiment children (n= 16), CTB (n=9) and VI (n=7), were given a set of 13 Mylar plastic raised-line outline pictures, extensively validated in previous research, depicting common objects (e.g., cup, happy face, bottle, etc.), to explore haptically (SVI blindfolded) and to name the represented object. Children speech was analyzed through tools offered by the CLAN (Computerized Language ANalysis) program. RESULTS: We found that, even though, generally, in the present task all children did not verbalize a lot, CTB children verbalized more and for longer than their SVI counterparts. Also, as reflected by CLAN analysis, CTB children’s speech was richer in utterances and number of words produced. We obtained similar results when we considered the semantic contents of the verbalizations. However, the verbalization pattern of both groups did not fully support Luria/Vygotsky hypothesis. While for both groups, a greater number of sentences were associated with complex pictures, which presented a relatively higher difficulty for object naming, in both groups, minimum or no verbalizations were associated with unidentified pictures. CONCLUSIONS: The trend that our results point out seems partly in accordance with the classical theory proposed by Luria/Vygotsky. Children with congenital total blindness manifest a wider range of verbalization, semantic and exploration abilities that seem associated with concurrent problem solving. The verbal and behavioral patterns observed in the CTB children are consistent with recent findings from the literature pointing at the cross-modal involvement of integrated brain regions which include frontal, parietal and occipital areas. In particular, the prominent role of speech in our data suggests that brain networks associated with Broca’s area could play a key role in compensatory plasticity by the mediation mechanism postulated by Luria/Vygotsky.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".