Bibliographic record
Abstract
This 450-hour advanced practicum took place with the Supportive Care Program (SCP) at the Northeast Cancer Centre (NECC) in Sudbury, ON. The social workers of the SCP provide emotional and practical support to individuals with a cancer diagnosis and their families. My learning focused on knowledge acquisition; improving direct practice skills; self-reflection; and was inspired by the question: how can I support cancer patients on an individual level, as well as, a systemic level? A generalist-eclectic approach was used during one-on-one counselling sessions in order to address the complex and varying needs of the cancer patients seeking services. Due to the COVID-19 pandemic, the majority of these sessions occurred via telephone or videoconference in order to adhere to social distancing guidelines and reduce the rate of transmission. In addition, a literature review was conducted exploring the impacts of systematic concerns within the Canadian healthcare system, as well as, the principles required to practice cultural humility and person-centred care. Social workers have a crucial role within oncology settings by supporting patients and encouraging the treatment of the patient as a whole in order to improve overall quality of life. The development of assertiveness skills are necessary to effectively advocate for patients, families, structural change, and the expertise of the social work profession. Social workers must also have an understanding of the historical systemic concerns present within our healthcare institutions informed by the core concepts of cultural humility.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.006 |
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".