Bibliographic record
Abstract
Making decisions on the basis of evidence is a central tenet of all health-care disciplines, including public health. However, it is not entirely clear what it means to base decisions on evidence; debates on evidence-based approaches often lack a clear understanding of the nature of evidence and obscure the normative underpinnings of evidence. Public health decision making requires an acceptance of limitations such as the availability of funding for research to provide complete evidence for any given decision, the ethical constraints on the creation of certain types of evidence and the ongoing dilemma between the need to take action and the need to gather more information. Using the example of the SARS outbreak in Canada, the inter-relationships between evidence and ethics are explored. I outline a set of critical questions for the global public health community to discuss regarding the nature of the relationship between evidence-based public health practice and ethics.
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 | 0.018 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.054 | 0.031 |
| Scholarly communication | 0.017 | 0.003 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".