Human Givens Therapy with adolescents: A practical guide for professionals by Yvonne Yates
Bibliographic record
Abstract
Very little is known about the personal side of life with cancer for young adults.Their autobiographical accounts can offer psychologists, healthcare professionals, caregivers, relatives, and other cancer patients valuable information beyond generalized health and social science data.In Everything changes, cancer patient and writer Kairol Rosenthal provides the reader with an honest, raw, and sometimes controversial insider's view on what it is like to be diagnosed with cancer in your 20s and 30s: 'By writing this book, I inspired to rip young adult cancer patients from the confines of these limited descriptors and perceptions.I want to reveal who we really are' (p. 7).By doing so, Rosenthal documents the interviews that she had with 25 other young cancer patients throughout the United States who had invited her for conversations.They retell their stories, holding nothing back, for the benefit of the reader.In addition, Everything changes is also a guidebook, accompanying the personal quotes and vignettes from interviews with these young adult cancer patients with lots of resources, including advice how to handle the (U.S.) healthcare system or access financial assistance.Young adult cancer patients are typically at a phase in their lives when they may have just moved out from their parents, are perhaps trying to establish independence, embark on postsecondary education or a professional career, begin to look for more stable partnerships, and some may think about raising a family.Many of these steps may be tentative, mixed with fears, confusions, desires, and hopes -and are invariably torn apart by a diagnosis of cancer.This is no different for author Kairol Rosenthal herself, originally a choreographer, who was diagnosed with second-stage thyroid cancer at age 27.Writing her book several years later, she recalls with a dramatic metaphor the day when she received 'the cancer bomb in her lap', her first thought being 'I want to stay alive long enough to get a dog' (p. 2) -a figment of at least some sense of continuity and belonging in the midst of chaos.And yet, fast-forwarding to the next morning, she does not quarrel 'why me', being diagnosed at such a young age, but, aware of cancer prevalence, 'why not me?'At the time of writing her book, Rosenthal has become a fully competent advocate for young cancer adult patients.The interviewees in her book comprise young adults with a broad range of cancer diagnoses, from breast cancer to lymphoma, cervical cancer, and other cancers.All of these participants grapple with their own fears and unspeakables, such as questions about parenting, attractiveness, mortality, career aims, living with parents, and dealing with pain, but also spirituality, intimate relationships, and friends.And while the intricacies of the healthcare system may seem to be
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".