Integrating workforce planning, human resources and service planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper is one in 10 in a series of papers commissioned by the World Health Organization to take stock of the state of the science of human resources for health activities in the year 2000. This paper provides an analysis of how labour market indicators can be integrated into service planning, discusses whether planning is sufficiently responsive and flexible to retain relevance and validity in rapidly changing health systems, describes different models and approaches to linking and integrating workforce planning and service planning, discusses methodological approaches to integrating planning, and examines effective approaches to the use of computer based scenario modeling to support assessment of current and future planning options. The context and broad cross-cutting themes of public sector, political, social, and macro-economic changes have been considered. Where publications exist, empirical evidence serves as the basis for this analysis and country examples have been highlighted. While strides have been made in the practice of resource planning world-wide, health human resource planning in most countries has been poorly conceptualized, intermittent, varying in quality, profession specific in nature, and without adequate vision or data upon which to base sound decisions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it