Features of alexithymia and behavior of children with learning disability in Anning City
Bibliographic record
Abstract
Objective To explore the features of alexithymia and behavior of children with learning disability(LD) and to provide evidence to ameliorate the learning disability.Methods One hundred and fifty-eight children from grade 3 to 6 of a primary school in Anning city were assessed as LD with the Pupil Rating Scale Revised-Screening for Learning Disability(PRS) and Multiple Achievement Tests(MATs).Another 158 children were taken as control group respectively from the normal children who were matched by sex,age,grade and class with LD children randomly.The children with LD and normal children were tested by the Alexithymia Questionnaire for Children(AQC) and the Conner' s children behavior scale parent' s questionnaire was assessed by their parents.Results Compared the AQC between children with learning disability and controls,the disorder of identification feeling(DIF),disorder of described feeling(DDF),extraversion outward thinking(EOT) factor scores in children with LD were higher.In the Conner' s Children behavior Scale,the morality,learning and psychosomatic problem,impulse hyperactivity,anxiety,hyperactivity index factor scores in children with LD were higher than those of controlled group.Conclusion The alexithymia exists in children with learning disability.Children with learning disability have more behavioral problems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".