Service, advocacy and adjudication: Balancing the ethical challenges of multiple stakeholder agendas in the rehabilitation of chronic pain
Bibliographic record
Abstract
PURPOSE: To highlight potentially conflicting roles of the rehabilitation professional in the treatment of clients with persistent pain conditions. In assisting clients requiring rehabilitation, the role of the rehabilitation professional is usually fairly clear and unambiguous. If however questions about the authenticity of the client's presenting disability have been raised, then a major role conflict can arise. Many clients present with symptoms of pain and disability yet there is no objectively discernible disease, and in these cases, the authenticity of the condition may be questioned. As rehabilitation professionals we may thus find ourselves acting in different roles: (i) We might be a clinical service provider working to reduce the client's suffering, (ii) We might become the client's advocate working to protect the client in conflicts with an insurer, (iii) We might become an adjudicator working to help the insurer detect evidence of our client's fraudulent behaviour. The principal objective of this paper is to distinguish these roles, and highlight their incompatibility. It is stressed that accreditation for and competence in clinical intervention does not guarantee or legitimize competence in advocacy or adjudication. CONCLUSIONS AND RECOMMENDATIONS: The paper concludes by suggesting that the primary role of the rehabilitation professional should be the provision of clinical service and that the adoption of the role of advocate or adjudicator may cross unacceptable ethical boundaries resulting in bringing harm, intentionally, or unintentionally, to the client.
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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 | 0.259 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.031 | 0.117 |
| Scholarly communication | 0.032 | 0.017 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.031 | 0.023 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".