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 Canada, the concept of monitoring and evaluation (M&E) is interpreted such that evaluation has a distinct identity from monitoring. The Canadian M&E system is one that has invested heavily in both evaluation and performance monitoring as key tools to support accountability and results-based management. Section two of the paper traces the evolution of the formalized use of M&E in Canada's public sector from its origins in the 1960s to the present day. Section three outlines the organization of M&E, identifying the key players at a government-wide level, as well as M&E organization within an individual government department. Section four highlights the key features that define the Canadian M&E system, characterizing the system on the basis of eight distinguishing elements. Section 5 provides information on the ways that M&E information has been used in the Canadian public sector, including recent efforts to strengthen the link to decision-making. Lessons learned from the Canadian experience with public sector M&E are summarized in section six under three broad categories: lessons regarding drivers for M&E; lessons pertaining to the implementation of the M&E system and; key elements associated with M&E capacity building.
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.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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