Non-monetary Awards for Public Sector Programs and Institutions : \nSurvey of Selected International Experience
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 guide presents a range of \n non-monetary award programs to recognize performance \n improvements in government programs, initiatives, and \n agencies. Nine award programs are drawn from Canada, \n Ireland, Abu Dhabi, the Philippines, the United States and \n Jordan. Each of the programs are analyzed along the \n following dimensions: objectives, target applicants, award \n categories, selection criteria, participation, selection \n process, type of reward, year of establishment, and number \n of awards given per year. Individual program details along \n these dimensions are available. The first section presents \n the theoretical background on how non-monetary award \n programs function, their expected benefits, and guiding \n principles to harness the potential benefits of such a \n program. The second section highlights the findings from the \n analysis of the nine programs along the key dimensions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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