Performance Management System Reform : Results-Based Budgeting in the Government of Alberta (2012-2014)
Bibliographic record
Abstract
This thesis examines the concept of performance management in the context of program evaluation and the management of public administration systems. The thesis begins by outlining and examining the common theoretical underpinnings of performance management. Once the theory is developed, the thesis reviews and identifies the key findings of the empirical literature that attempts to identify and explain the variables that impact the implementation of performance management systems. Following this the contemporary case of Results-Based Budgeting (RBB) in the government of Alberta is examined and contrasted with the theory. The examination of RBB in Alberta reveals that the theoretical literature is useful for classifying performance management systems in practice, but that the possible outcomes of performance management reform extend beyond the typical purported benefits of efficiency, effectiveness, and accountability associated with the rational actor model of performance management. In Alberta, some of the outcomes of RBB include horizontal integration, strategic policy alignment, and cultural change. Alberta’s experience with RBB also supports the constructivist model of performance management, which suggests that these systems contribute to public sector organizations by structuring policy analysis and dialogue, enhancing strategic planning, and other benefits.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".