Bibliographic record
Abstract
Purpose – The purpose of this paper is to describe recent passage of a private member's bill that can put Canada on a different path from the USA in attempting to resolve conflict that arose over how an influential clinical practice guideline for Lyme disease was developed. Design/methodology/approach – Narrative review. Findings – Critical appraisal of pertinent scientific literature is fundamental to the production of evidence-based practice guidelines. Perception of fairness and transparency in a guideline development process is fundamental to wide acceptance. Allegations of conflicts of interest and excluding opposing views in development of Lyme disease guidelines led to legislative interventions after insurers started basing denial of claims and licensing boards started responding to complaints against physicians whose treatment regimens were inconsistent with guideline statements on chronic Lyme disease. Opposing sides are both faced with limitations in available research evidence. Claims and counterclaims about availability of impartial subject matter experts free of vested interests arose; however, this has been compounded by failures in communication channels. Perhaps most importantly, and the focus of this viewpoint, wide perception among those afflicted of a flawed guideline development process makes it unlikely that all sides can reach agreement on this path. Canada, unlike the USA, is taking steps to include all stakeholders (including representatives of the medical community and of patients’ groups) in a review meeting to develop a comprehensive national framework. Research limitations/implications – This situation provides a noteworthy example of defining best practice in the difficult situations where stakes are high, diagnostic tools are flawed, some of those identified as experts have vested interests, and patients with unmet needs feel excluded. Originality/value – The next steps in Canada bear watching, both in terms of potentially resolving key conflicts around the one guideline document in question, and also as a potential model for a more successful guideline development process.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".