Paradigms of Health and Disease: A Framework for Classifying and Understanding Complementary and Alternative Medicine
Bibliographic record
Abstract
The number of complementary and alternative medicines (CAMs) being utilized by North America health care consumers is growing at an astounding rate. There is a need by both health care providers and consumers to categorize CAM in order to make meaningful comparisons and informed decisions on their use. Four paradigms of health and illness are proposed that classify medicines according to the basic assumptions of health and disease associated with each medicine. CAMs classified in the body paradigm are those that work through biologic mechanisms, or in other words, target biologic factors as the primary determinants of health. The mind-body paradigm extends the body paradigm to include factors such as stress, psychologic coping styles, and social supports as primary determinants of health and disease. The body-energy paradigm assumes health and disease are functions of the flow and balances of life energies. The body-spirit paradigm assumes that one or more transcendental aspects or personalities existing outside the limitations of the material universe can influence health and disease. It is postulated that there is a hierarchical relation among the four paradigms, such that each paradigm essentially subsumes the assumptions of the previous ones, but adds additional assumptions that qualify the previous ones. Implications of this framework for clarifying many contemporary issues in health care are discussed.
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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 | 0.014 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.010 | 0.021 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| 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 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".