Treating real people: Science and humanity
Bibliographic record
Abstract
Something important is happening in applied, interdisciplinary research, particularly in the field of applied health research. The vast array of papers in this edition are evidence of a broad change in thinking across an impressive range of practice and academic areas. The problems of complexity, the rise of chronic conditions, overdiagnosis, co-morbidity, and multi-morbidity are serious and challenging, but we are rising to that challenge. Key conceptions regarding science, evidence, disease, clinical judgement, and health and social care are being revised and their relationships reconsidered: Boundaries are indeed being redrawn; reasoning is being made "fit for practice." Ideas like "person-centred care" are no longer phrases with potential to be helpful in some yet-to-be-clarified way: Theorists and practitioners are working in collaboration to give them substantive import and application.
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 | 0.019 | 0.093 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.024 | 0.013 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.019 | 0.044 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".