Health Care Reform: Opportunities for Professional Chaplains to Build Intentional Communities of Learners by Integrating Faith, Science, Quality, and Systems Thinking
Bibliographic record
Abstract
Albert Einstein once said, "The significant problems we face cannot be solved at the same level of thinking we were at when we created them" (www.brainyquote.com). Health care reform has brought professional chaplains to a place of chaos-a place that raises many questions about the past, present and future. This chaos presents tremendous opportunities for professional chaplains to increase their capacities in building intentional communities of learners by integrating faith, science, quality and systems thinking. Pastoral care givers must truly understand the pressures from all sides and the new emerging paradigm of integrated health care delivery. Without this understanding, we will not see the opportunities and challenges of integrating pastoral and spiritual care in the emerging structures and systems. The future of chaplaincy largely will depend on the quality of the data, quality of our conversations and our ability to thinking together through dialogue.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.040 | 0.036 |
| Insufficient payload (model declined to judge) | 0.009 | 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".