Examining the importance of advance care planning and therapy supervision models within a cancer centre
Bibliographic record
Abstract
This advanced practicum document reviews my experience with the Supportive Care Program (SCP) at the Northeast Cancer Centre (NECC) in Sudbury, Ontario. This practicum provided both project work and clinical opportunities. The project work consisted of two advance care planning projects: an environmental scan of cancer centres across Ontario and a chart audit that was specific to the NECC. These projects demonstrate the need for standardizing the process of advance care planning (ACP), as both projects demonstrated inconsistencies of current advance care planning standards within healthcare settings. An overview of current literature demonstrates the importance of incorporating ACP into every day healthcare conversations, as it can help promote patient care. In addition to the ACP projects, I also worked in collaboration with the social workers of the Supportive Care Program to create a new therapy supervision model. This model incorporated practices of reflectivity and debriefing, promoting supportive supervision. Through a combination of the literature as well as discussions with the social workers, together we were able to determine how supportive supervision would not only benefit the social workers but would also aid in patient service. This document also explores my shadowing and clinical experiences. Reviewing my work within a multidisciplinary team, I demonstrate how this work model added to my clinical experience, while aiding in patient care. This document also discusses the professional and personal growth that I gained through working with persons with cancer and their family’s, through reviewing my reflection of my experience.
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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 | 0.021 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".