The evolution of <scp>GRADE</scp> (part 3): A framework built on science or faith?
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) framework has undergone several modifications since it was first presented as a method for developing clinical practice recommendations. In the previous two articles of this series, we showed that absent, in the first three versions of GRADE, is a justification (theoretical and/or empirical) for why the presented criteria for determining the quality of evidence and the components for determining the strength of a recommendation were included (and others not included) in the framework. Furthermore, it was often not clear how to operationalize and integrate the criteria/components when using the framework. In part 3 of this series, we examine the literature since version 3 to see if the GRADE working group has provided an overall justification scheme for GRADE or clear instruction on how to operationalize and integrate the criteria/components in the framework. METHODS: Narrative review. RESULTS: GRADE has undergone further modification since the last version was presented. In the recent literature, we see additional shifts in terminology (eg, "quality of evidence" is now "certainty of evidence"), clarification on the construct of certainty of evidence, continued emphasis on "transparency" and new emphasis on "trustworthiness," the addition of health equity as a component for determining strength of a recommendation, and the development of the Evidence to Decision frameworks. However, these modifications have done little to improve the justification scheme that sustains GRADE or clarify how to operationalize the criteria/components. CONCLUSIONS: If we desire that our clinical recommendations be based on scientific teaching rather than faith-based preaching, then the GRADE framework should be justified theoretically and/or empirically. Until such time that the working group provides a theoretical justification that the use of the GRADE framework should produce valid recommendations, and/or empirical evidence to support that it does, enthusiasm for the framework should be tempered.
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 | 0.446 | 0.700 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.020 | 0.023 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.036 | 0.025 |
| Open science | 0.016 | 0.018 |
| Research integrity | 0.023 | 0.044 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".