Federation of Canadian Municipalities Quality of Life Reporting System, measures of community affordability
Bibliographic record
Abstract
Despite a longstanding interest in measuring the quality of our life there is a lack of consistent tracking and reporting of social issues on a national scale. The Federation of Canadian Municipalities (FCM), in an attempt to rectify this problem, worked in conjunction with sixteen municipalities to develop a framework from which to monitor Quality of Life in Canadian municipalities. The FCM Quality of Life Reporting System is comprised of ten indicators. This practicum focuses on the design, development and implementation of just one of the indicators, community affordability. The purpose of the Community Affordability Measure (CAM), is to measure the relative affordability of Canadian communities and changes in their relative affordability over time for both the community as a whole (CAM 1), and for what is referred to in this study as the 'modest income population' (CAM 2). The CAM is an index of the ratio of the income of the residents to the cost of living within the municipality compared to the aggregated experience of all the participating municipalities. This measure allows municipalities to determine where they stand on a national basis in relation to the quality of life their residents can afford. The initial results have provided baseline quantitative data from which future changes will be tracked and reported.
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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.013 | 0.020 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".