The Effectiveness of the Dealing with Homophobia Psycho-Education Program on Psychological Counselor Candidates
Bibliographic record
Abstract
The aim of this research is to investigate the effect of the Dealing with Homophobia Psycho-Education Program on homophobia levels of psychological counselor candidates. This research was conducted with a mixed model and utilized quantitative and qualitative methods. 2 (experimental and control groups) x 3 (pre-test, post-test, follow-up) research design which is a type of quasi-experimental design was used and content analysis was applied to the data obtained via interviews. The study was conducted with a total of 24 psychological counselor candidates, 12 in the experimental group and, 12 in the control group. The Homophobia Scale was used to determine the homophobia levels of psychological counselor candidates. The Dealing with Homophobia Psycho-Education Program was developed by the researcher. In order to determine the effectiveness of the program, The Two-Way Analysis of Variance with Repeated Measures was used. As a result of the research, it was determined that the Dealing with Homophobia Psycho-Education Program is effective in decreasing the levels of homophobia of the psychological counselor candidates. Also, according to the participant's views, it was determined that the psycho-education program was effective in decreasing homophobia and caused changes in attitudes. The importance and necessity of using the program on psychological counselor education are 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".