A study on the supervision needs of multi disciplinary teams in outpatient mental health programs in Northwestern Ontario
Bibliographic record
Abstract
The central research question for this thesis is: What are the supervisory needs of front line staff from the perspective of members of multi disciplinary teams in Northwestern Ontario. The objectives of this research are (1) to determine the process of supervision in multi disciplinary teams; (2) to determine what works well in the supervisory process of multi disciplinary teams; (3) to determine what does not work well in the supervisory process of multi disciplinary teams; and (4) to provide recommendations that could enhance the supervisory process for members of multi disciplinary teams. Qualitative research methodology in the form of in depth interviews with 14 front line mental health workers was used to collect data. The specific method of inquiry was a modified phenomenological study. Participants were asked to share their experiences of supervision in the context of multi disciplinary teams in adult mental health programs. Almost all respondents saw value in having didactic supervision with their supervisor, however for many this wa not their reality. Front line staff, commented on the merit of one on one supervision, staff evaluations, trusting supervisory relationships, the importance of peer supervision and a formalized debriefing process. In the absence of traditional supervisory processes many of those interviewed found creative ways to get their supervisory needs met including the use of technology. This thesis reports on issues pertaining to professional identity in the context of multi disciplinary teams. Several front line staff discuss the erosion of their professional identity as they became immersed in their role as therapist. My research also offers insights into these workers experiences as it pertains to implications for social work practice, policy and education.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".