A Stuttering Education and Bullying Awareness and Prevention Resource: A Feasibility Study
Bibliographic record
Abstract
PURPOSE: This pretest-posttest study examined the feasibility of using a curriculum-level stuttering education and bullying awareness and prevention program to improve peer attitudes toward children who stutter and attitudes toward bullying. Knowledge about potential responses to bullying and students' liking of the program also were examined. METHOD: Data were obtained from 608 children who participated in the stuttering education and bullying prevention initiative that used the Teasing and Bullying: Unacceptable Behaviour (TAB; Langevin, 2000) Program. Participants completed the Peer Attitudes Toward Children Who Stutter (PATCS; Langevin, 2009; Langevin & Hagler, 2004; Langevin, Kleitman, Packman, & Onslow, 2009) scale, the Provictim scale (Rigby & Slee, 1991, 1993), and bullying involvement and knowledge questionnaires. RESULTS: Statistically and practically significant improvements were found for both questionnaires. Children who did not know someone who stutters had higher change scores on the PATCS than children who knew someone who stutters. In general, children who were uninvolved in bullying had the most positive changes in attitudes and liked the TAB program the most. Victims liked the program significantly more often than children who were perpetrators of bullying or were dually involved in bullying. CONCLUSION: Findings suggest that the TAB program may have the potential to effect positive changes in peer attitudes toward children who stutter and toward bullying. Further research using a randomized experimental design is warranted.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".