Life Care Plan Survey 2022: Process, Methods, and Protocols – a 20-Year Perspective
Bibliographic record
Abstract
The purpose of this research is to update the Life Care Planning Surveys of 2001 and 2009 with longitudinal data over the course of 20 years regarding the process, methods, and protocols of life care planning. This research provides data to support and advance the practice of life care planning. The Life Care Plan Survey 2022 is a revision and replication of the 2001 and 2009 life care planning surveys. Areas addressed in the survey included: a) demographics; 1. b) business practices; c) roles and functions of the life care planner; 2. c) life care planning protocols; and e) future growth and development. Survey results describe the current state of life care planning practice; provide data on protocols/procedures used by life care planners; and identify areas of life care planning practice where further definition, refinement and/or research may be necessary. In addition to descriptive data, responses were analyzed in terms of similarities and differences related to field of practice, certification status, and amount of deposition experience. Results are expected to enhance life care planning practice by promoting continued discussion and consideration regarding roles, scope of practice, competencies, and standards of practice.
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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 | 0.484 | 0.319 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".