Joining public accountability and performance management: A case study of Lethbridge, Alberta
Bibliographic record
Abstract
Abstract: This article presents an in-depth assessment of how performance measurement, public reporting, and internal performance management have been merged in Lethbridge, Alberta. Business-unit managers and council members both share the view that performance measurement and reporting are useful and that performance information is credible. This finding contrasts with the more general view that performance information is not used much, despite widespread commitments to collecting it. In Lethbridge, a balance has been struck between performance measurement for management uses and council uses. The current system is driven by managers who share the view that performance measurement and reporting are useful for improving programs and providing information that can be a part of public accountability. If performance measurement is to add value in public-sector organizations, it needs to have the continued support of managers – they are key to developing the measures, collecting the information and using it, and sustaining such systems. Changes that undermine the trust that is critical to a workable compromise for performance measurement, public reporting and performance management ultimately undermine the integrity of these systems.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".