Missing Persons Alert: Finding the Lost “Person” in Patient-Oriented Research
Bibliographic record
Abstract
After a decade of attempts at patient-oriented research, this article seeks to advance the approach, making individuals and communities active partners in health research. Patient-oriented research remains inconsistently implemented, tokenistic, and met with resistance-largely due to the system in which it was conceived and practiced. Patients remain bound by object-oriented medical cosmologies, thus reaffirming the hierarchical system underpinned by professional dominance. Until health research and researchers develop an awareness of the subtle injustices legitimized by the current approach, patient-oriented research will not actualize its mandate. This article does not challenge the healthcare system as that is beyond its scope; instead, it aims to develop further the "what" and "how" of public involvement in health research through the supplement of participatory research methodologies. In effect, setting the early foundations for transformation and encouraging a transition to a more just and equitable healthcare and research ecosystem.
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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 | 0.247 | 0.227 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.037 | 0.125 |
| Scholarly communication | 0.036 | 0.071 |
| Open science | 0.006 | 0.047 |
| Research integrity | 0.017 | 0.034 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".