Performance Measurement Program Results for information.
Bibliographic record
Abstract
MPMP is a performance measurement and reporting system that promotes local government transparency and accountability. It also provides municipalities with useful data to make informed municipal service level decisions while optimizing available resources. All Ontario municipalities are required to report MPMP efficiency and effectiveness measures for services provided by their municipality. The program contributes to improved delivery of municipal services across Ontario by providing a standardized set of efficiency and effectiveness measures for key service areas. By reporting MPMP results to the public, Ontario municipalities are achieving a level of transparency and accountability which has gained both national and international recognition. All municipalities are required to report data for 2013 MPMP measures to the Ministry by May 31, 2014 and to the public by September 30, 2014. Municipalities are asked to notify their regional Municipal Services Office of the date when and method how they reported their MPMP results to the public. Municipalities determine the best way to report to the public and can use the reporting templates provided by the Ministry. For the 2013 reporting year, MPMP measures are the same as those for 2012 – with the exception of measures for Building Permits and Inspection Services. After reviewing historical MPMP data, and in consultation with municipal experts, the Ministry has revised these measures so that they provide a clearer picture of municipal practices. The MPMP is a tool for comparison of results, which can help start a dialogue and advance local government priorities of efficiency and effectiveness in service delivery and accountability to the public.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".