Difficult decisions in times of constraint: Criteria based Resource Allocation in the Vancouver Coastal Health Authority
Bibliographic record
Abstract
OBJECTIVES: The aim of the project was to develop a plan to address a forecasted deficit of approximately $4.65 million for fiscal year 2010/11 in the Vancouver Communities division of the Vancouver Coastal Health Authority. For disinvestment opportunities identified beyond the forecasted deficit, a commitment was made to consider options for resource re-allocation within the Vancouver Communities division. METHODS: A standard approach to program budgeting and marginal analysis (PBMA) was taken with a priority setting working committee and a broader advisory panel. An experienced, non-vested internal project manager worked closely with the two-member external research team throughout the process. Face to face evaluation interviews were held with 10 decision makers immediately following the process. RESULTS: The recommendations of the working committee included the implementation of 44 disinvestment initiatives with an annualized value of CAD $4.9 million, as well as consideration of possible investments if the realized savings match expectations. Overall, decision makers viewed the process favorably and the primary aim of addressing the deficit gap was met. DISCUSSION: A key challenge was the tight timeline which likely lead to less evidence informed decision making then one would hope for. Despite this, decision makers felt that better decisions were made then had the process not been in place. In the end, this project adds value in finding that PBMA can be used to cover a deficit and minimize opportunity cost through systematic application of criteria whilst ensuring process fairness through focusing on communication, transparency and decision maker engagement.
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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 | 0.038 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".