What School Counselors Say: Training Needs for Preventing Child Sexual Abuse
Bibliographic record
Abstract
The goal of the present study was to understand the current needs of school counselors for preventing child sexual abuse. The need assessment study was carried out with a focus group sample. The participants were school counselors who work in various types of schools. The researcher contacted the school counselors and invited them to participate in the research. During the focus group meetings, the researcher collected the data through audio recordings and later transcribed them. Content analysis was used to generate codes, and codes were grouped into subthemes, which were used to identify themes. Focus group data were categorized according to three themes: 1) the perceptions of school counselors’ role in preventing abuse; 2) the issues that school counselors' feelings of inadequacy in preventing abuse, and 3) the recommendations for the future prevention programs. Based on the results of the study, school counselors had limited theoretical knowledge and professional competence regarding child sexual abuse. The results also revealed that some prevention programs in Turkey were available but insufficient to meet the needs of school counselors. Moreover, the researcher discussed implications for future research and practice were discussed.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".