Problems for clinical judgement: 5. Principles of influence in medical practice.
Bibliographic record
Abstract
The basic science of psychology has identified specific ingrained responses that are fundamental elements of human nature, underpin common influence strategies and may apply in medical settings. People feel a sense of obligation to repay a perceived debt. A request becomes more attractive when preceded by a marginally worse request. The drive to act consistently will persist even if demands escalate. Peer pressure is intense when people face uncertainty. The image of the requester influences the attractiveness of a request. Authorities have power beyond their expertise. Opportunities appear more valuable when they appear less available. These 7 responses were discovered decades ago in psychology research and seem intuitively understood in the business world, but they are rarely discussed in medical texts. An awareness of these principles can provide a framework for physicians to help patients change their behaviour and to understand how others in society sometime alter patients' choices.
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 | 0.145 | 0.352 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.010 | 0.014 |
| Research integrity | 0.029 | 0.017 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".