A Selective Critical but Constructive Desktop Appraisal of the<i>American Medical Association Guides to the Evaluation of Permanent Impairment (AMA 6)</i>
Bibliographic record
Abstract
Abstract This desktop review has been conducted, from the reviewers' perspective, to evaluate the merits, advantages and disadvantages of adopting the 6th edition of theAmerican Medical Association (AMA6) Guides for the Evaluation of Permanent Impairment.The reviewers do not make any recommendation as to whetherAMA6should or should not be adopted by any particular jurisdiction, but rather provide comment from the perspective of a critical but constructive appraisal of published material. The observations reported represent the opinions of the reviewers, based on their appraisal of selected sections ofAMA4,AMA5andAMA6and the associated literature.AMA6has become surrounded by considerable controversy. At the time of review, at least two jurisdictions in the United States have voted against adoption ofAMA6. While the paradigm shift away from the World Health Organization (WHO) International Classification of Impairment, Disability and Handicap (ICIDH) framework to the WHO International Classification of Functioning, Disability and Health (ICF) framework has attempted to ‘move with the times’, andAMA6has attempted to reach higher levels of internal consistency and interrater and intrarater reliability, the methods used to achieve a radical change in theGuideshas come under criticism. It is quite difficult to distinguish between speculative and substantive criticism, because of paucity or obscurity in both source documents and subsequent commentary. A range of concerns have been identified.
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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 | 0.353 | 0.753 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.022 | 0.015 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.023 | 0.009 |
| Open science | 0.010 | 0.007 |
| Research integrity | 0.015 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 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".