Health services research: building capacity to meet the needs of the health care system
Bibliographic record
Abstract
Health services researchers have an important role to play in helping health care systems around the world provide high quality, affordable services. However, gaps between the best evidence and current practice suggest that researchers need to work in new ways. The production of research that meets the needs and priorities of the health system requires researchers to work in partnership with decision-makers to conduct research and then mobilize the findings. To do this effectively, researchers require a new set of skills that are not conventionally taught as part of doctoral research programmes. In addition to wider contextual changes, researchers need to understand better the needs of decision-makers, for example through short placements in health system decision-making settings. Second, researchers need to learn to accommodate those needs throughout the research process, including identifying research needs; conducting research collaboratively with decision-makers and producing effective research products.
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 | 0.232 | 0.210 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.012 | 0.049 |
| Scholarly communication | 0.030 | 0.043 |
| Open science | 0.011 | 0.065 |
| Research integrity | 0.019 | 0.020 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".