Music Therapists’ Perspectives on how Self-Awareness \nImpacts their Work with Adolescents
Bibliographic record
Abstract
A significant body of research indicates that self-awareness is recognized as a vital aspect in a therapist’s career. In a music therapy setting, self-awareness is also identified as a crucial aspect for music therapists who work with the adolescent population. However, studies have not yet established how music therapists’ self-awareness impacts their sessions when working with adolescents. Using a modified grounded theory method, this research investigated music therapists’ perspectives on how self-awareness impacts their work with adolescents. It comprised interviews of four board certified music therapists working with adolescents in the medical and/or mental health settings. Interview transcriptions were coded using methods from Hesse-Biber (2011). Comparisons were made of participants’ perceptions of self-awareness, reactions when self-aware, and influence of self-awareness during music therapy sessions with adolescents. Results indicated that music therapists address self-awareness personally and in regards to clients in order to adjust in the moment. Further research is recommended in order to explore self-awareness practices among music therapists and its complexity in greater detail. It is the researcher’s hope that music therapists utilize the findings of this research study to expand on and become more aware in their practice with specific populations of adolescents.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".