Social Support in Post Secondary Institutions for Post-Cancer Adolescents
Bibliographic record
Abstract
In this article, the researcher looks for various social support services offered at, or by, post-secondary institutions in northern Alberta, for adolescents and young adults (AYAs) who have survived cancer. Due to the cancer treatments, AYAs suffer from several types of effects, both physical and psychological, such as depression, posttraumatic stress disorder, organ damage, cardiotoxicity and obesity. Since cancer treatment is a long and difficult process, AYAs miss extended periods of school and everyday youth experiences, leading to social isolation. By combining social isolation with other physical and psychological effects, AYAs are left in a state of suspension between the maturity they gained by making adult decisions regarding their treatment, and their different social tendencies compared to peers due to missed experiences. Research was conducted on the internet, looking at eight post-secondary websites to find educational and social support services for cancer survivors. Findings revealed no specific services garnered towards post cancer AYAs, but a myriad of various other services for both ‘normal’ students, and students with disabilities. Peer led groups and counselling geared towards post-treatment of illnesses/diseases needs to be implemented in post-secondary institutions to help AYA cancer survivors handle the complex situation of being a cancer survivor, with the added stress of being a post-secondary student. Discipline: Sociology Faculty Mentor: Dr. Diane Symbaluk
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".