From Rivalry to Rapprochement: Bio-Medicine, Complementary Alternative Medicine (Cam) at Ethical Crossroads
Bibliographic record
Abstract
Against the backdrop of the political intrigue in bio-medicine's ascendancy to orthodoxy, this article examines its contemporary rapprochement with Complementary Alternative Medicine (CAM), in the move toward an integrated medical regime. It also identifies and explores factors underlying the rapprochement, as well as different ethical challenges that face integrated medicine. It argues that a major approach to tackling these challenges hinges on devising just and equitable criteria for evaluating the efficacy of plural therapeutic paradigms inherent in CAM models. This is attainable through a policy that encourages creating public health policy and medical personnel deliberately exposed as part of their curriculum to the philosophical and theoretical features of diverse therapeutic traditions.
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.
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 | 0.035 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.088 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".