Bibliographic record
Abstract
Despite basing its foundation upon the ideals of Hippocrates, Western medicine, especially in the last century, has shifted from a holistic to a more reductionist approach to understanding and treating patients. These changes are primarily a result of widespread acceptance of the biomedical model in modern medicine. Consequently, there are now significant differences in physician and patient explanatory models for the same ailment. Cancer, for example, is interpreted as primarily a physiological process by the medical community, or more simply, as a disease. The patient, on the other hand, interprets cancer as an illness, a more subjective response, covering all aspects of the patient’s life experience, including emotional, psychological, social, and cultural realms, in addition to physiological aspects. These differences in explanatory models result in disparities between physicians and patients when it comes to defining the condition, managing the condition and even defining successful outcomes. These incongruencies must be addressed through effective communication in the clinical encounter, an aspect of patient care that has proven beneficial effects on patient health outcomes. The shared treatment decision-making model best addresses these communication problems. By providing a framework for both the physician and patient to negotiate their respective explanatory models en route to a mutually agreeable treatment decision, this model is a compromise between the two extremes of patient-physician models of communication: paternalism andinformed decision-making. Ultimately, the shared treatment decision-making model establishes a clinical relationship that is no longer characterized by an inabilityto effectively negotiate and consolidate differing values due to unbalanced informational and power dynamics in a social context. By incorporating this model of communication into medical practice, physicians and patients will better understand each other, bridging the disparities apparent in current practice and allow Western medicine to once again approximate the Hippocratic ideal.
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 | 0.078 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.018 | 0.026 |
| Scholarly communication | 0.018 | 0.035 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.013 | 0.024 |
| Insufficient payload (model declined to judge) | 0.008 | 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".