Comparing a discriminative stimulus procedure to a pairing procedure: Conditioning neutral social stimuli to function as conditioned reinforcers.
Bibliographic record
Abstract
Social stimuli that function as reinforcers for most children generally do not function as reinforcers for children diagnosed with autism. These important social stimuli include smiles, head nods, thumb-ups, and okay signs. It should be an important goal of therapy for children with autism to condition these neutral social stimuli to function as reinforcers for children diagnosed with autism. There is empirical evidence to support both a pairing procedure (classical conditioning) and a discriminative stimulus procedure to condition neutral stimuli to function as reinforcers. However, there is no clear evidence as to the superiority of effectiveness for either procedure. Despite this most textbooks and curriculum guides for children with autism state only the pairing procedure to condition neutral stimuli to function as reinforcers. Recent studies suggest that the discriminative stimulus procedure may in fact be more effective in conditioning neutral stimuli to function as reinforcers for children diagnosed with autism. The present research is a further comparison of these two procedures. Results from one participant support recent findings that suggest the discriminative stimulus procedure is more effective in conditioning neutral stimuli to function as reinforcers. But the results from the other participant show no effects from either procedure, suggesting future research into conditions necessary to condition neutral social stimuli to function as reinforcers for children with autism.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".