A quality function deployment–based resource allocation approach for elderly care service: Perspective of government procurement of public service
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
In response to the rapidly growing demand for elderly care service in China, rational allocation of limited resources and improvement of public satisfaction have become one of the urgent problems to be solved in government procurement of elderly care services. With the aid of quality function deployment, a programming model is established to allocate resource with maximizing customer satisfaction. Taking home care service as an example, on the basis of identifying the elderly’s requirements, designing attributes, optimal allocation of limited resource is conducted based on the proposed approach. Results show that staff in the home care service center should pay more attention to improve their service attitude and service quality. Meanwhile, more resources should also be allocated to improve the specialization of the franchise center, and to increase the provision of professional medical personnel and purchase of common medicines for emergencies as well as facilities for rehabilitation. This study expands the field of elderly care service by introducing a more efficient resource-allocation approach, thus helping governments in decision-making.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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