Teaching Lexical Humor to Children with Autism
Bibliographic record
Abstract
Comprehension and production of linguistic humor is an important social, linguistic, and cognitive skill for all children, but it often fails to develop in children with autism. One form of linguistic humor that is based on multiple meaning words and can take the form of riddles or jokes has been identified as “lexical humor.” This study investigated the effects of the Lexical Humor Treatment Program (Gill, White, & Reyes, 2010) on six high-functioning children with autism. All of the children increased their understanding of multiple-meaning words and their ability to answer related riddles on which they had been trained. More importantly, the children were able to transfer their skill in practiced riddles to novel riddles on which they had not been trained. These results suggest that the teaching of humor in the form of lexical riddles might be an important treatment consideration for children with autism. Key words : Lexical Humor; Linguistic Humor; Autism; Asperger Syndrome; Riddles; Multiple Meaning Words; Humor Instruction
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".