AN EXPLORATION INTO ADDICTIONS COUNSELLOR TURNOVER IN MANITOBA: A NARRATIVE INQUIRY
Bibliographic record
Abstract
Addiction is a growing concern particularly in Manitoba where the rate is higher than the national average. Individuals are accessing addictions services at steadily increasing rates therefore Counsellors will be needed to deal with this increase. International literature reports high turnover among addictions counsellors, with detrimental effects on service delivery. This thesis aims to enhance an understanding of the ways in which contextual features influence how and when counsellors leave the field of addiction. A critical narrative approach was adopted that aligned with a constructivist paradigm. Two semi structured narrative interviews were conducted with four participants. Common themes that emerged were: education playing a major role in the difficulties experienced by the participants, the impact of centralized decision-making, lack of support from management and coworkers, systemic constraints making work in addictions challenging, as well as each participant being uncertain about entering, leaving and returning to the field of addictions. Findings indicate that turnover is non-linear and contextually situated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.010 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".