End-of-life issues, grief, and bereavement : what clinicians need to know
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Contributors. Preface. 1 Introduction to End-of-Life Care for Mental Health Professionals (Julia E. Kasl-Godley). 2 Trajectories of Chronic Illnesses (Michelle S. Gabriel). 3 The Cultural Context of Spirituality and Meaning (E. Alessandra Strada). 4 Working With Family Caregivers of Persons With Terminal Illness (David B. Feldman and Jasmin Llamas). 5 Serious Mental Illness (Julia E. Kasl-Godley). 6 Advance Care Planning (Michelle S. Gabriel and Sheila Kennedy). 7 Pharmacologic Management of Pain (W. Nat Timmins). 8 Nonpharmacological Approaches to Pain and Symptom Management (Stephanie C. Wallio and Robert K. Twillman). 9 Grief and Bereavement Care (Shirley Otis-Green). 10 Complicated Grief (E. Alessandra Strada). 11 Health-Care Teams (Julia E. Kasl-Godley and Donna Kwilosz). 12 End-of-Life Care in Long-Term Care Settings (Mary M. Lewis). 13 Advocating for Policy Change: The Role of Mental Health Providers (Robert K. Twillman and Mary M. Lewis). 14 Physician-Assisted Suicide in the United States: Issues, Challenges, Roles, and Implications for Clinicians (Silvia Sara Canetto). 15 Creating Ethics Conversations in Community (Malham M. Wakin). 16 Professional Self-Care (E. Alessandra Strada). 17 Embracing the Existential Invitation to Examine Care at the End of Life (Shirley Otis-Green). Author Index. Subject Index.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it