Repositioning Individualized Homeopathy as a Psychotherapeutic Technique With Resolvable Ethical Dilemmas
Bibliographic record
Abstract
The author puts forth the argument that the complementary and alternative medicine community should endorse specific aspects of the entire individualized homeopathic process, including its unique holistic consultation process, having dedicated lengths of time to enumerate the complete illness context, and the prescribing of homeopathic remedies, to reposition this modality as a psychotherapeutic technique. Moreover, placebo effects derived from homeopathic remedies could be used to further exploit favorable therapeutic effects that have accrued from the entirety of the homeopathic consultation process. The overall aim of this bold shift is to sustain the clinical practice of homeopathy from an ethical and clinically responsible (and plausible) framework that is properly evidence-informed.
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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 | 0.074 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.112 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.017 | 0.022 |
| 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".