A Lexicon of Concepts of Humanistic Medicine: Exploring Different Meanings of Caring and Compassion at One Organization
Bibliographic record
Abstract
PURPOSE: There has been scant scholarly attention paid to characterizing how the numerous definitions of terms associated with compassion and humanism have been mobilized or what the organizational implications of pursuing different constructs might be. This study explored the uses and implications of the terminology associated with humanistic medicine in the work of the Associated Medical Services (AMS) Phoenix Project. METHOD: This study involved two phases (2014-2015). First, two pilot group workshops with AMS Phoenix Project participants and stakeholders were conducted to explore ways of parsing and interpreting core concepts used in the project. The authors then assembled an archive of texts associated with the project, comprising the project website and blog posts, conference proceedings, and fellowship and grant applications. Informed by critical discourse analysis, the authors identified, described, and analyzed core terms related to the project's mission and explored the type of health care practices and reforms implied by their use. RESULTS: Two recurring core terms, care/caring and compassion, and eight clusters of terms related to these core terms were identified in the archive. Caring and compassion as terms were articulated in various psychological, sociological, and political configurations. This polysemy reflected a diverse array of health care reform agendas. CONCLUSIONS: Understanding how different interpretations of caring and compassion cluster around core topics and concerns of humanistic medicine offers scholars an entry point for comparing and appraising the quality and direction of reform agendas, including multilevel strategies that involve systems-level changes.
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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".