Bibliographic record
Abstract
H earns, klein and colleagues set out to develop a maternity care decision-making tool for the British Columbia Northern Health Authority to assist with assessing community needs and values.They are to be commended for thinking outside the traditional decision-making approach which focuses, as they say, on "administration, fiscal and safety issues.solutions often follow previously made decisions … [because] this approach is less time-consuming, simpler and safer."They go on to point out the problems with this approach, such as minimal engagement of community members or representation of their interests, potentially resulting in disempowerment and bitterness.They claim that their process rectifies this lack of engagement:Commentary on Development of a Support Tool for Complex Decision-Making Commentaire sur la mise au point d'un outil d' appui à la prise de décisions complexes
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 | 0.064 | 0.295 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.026 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.016 | 0.011 |
| Research integrity | 0.073 | 0.113 |
| Insufficient payload (model declined to judge) | 0.017 | 0.010 |
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".