Evaluation Report: 2010-2015 Social Development Strategy
Bibliographic record
Abstract
In 2010, Centraide of Greater Montreal adopted a strategy to fight poverty and social exclusion that was firmly grounded in a territorial approach.The hypothesis: Centraide could generate better outcomes by prioritizing investment targets and applying strategic and proactive investment approaches across a neighbourhood instead of considering agencies in isolation.Five years later, an evaluation was conducted in six communities to observe changes and draw lessons from this approach.Instead of just increasing resources so that agencies can do more, the territorial approach helped Centraide create a plan for each neighbourhood and use available vectors to support the desired improvements. These vectors include: * Support for solid and dynamic agencies that provide leadership in their communities. * Support for multi-network and intersectoral coordination so that communities can implement solutions that have the greatest chance of reducing and mitigating the impact of poverty and social exclusion. * Reinforcement of agency skills and leadership. * Ongoing relationships between organizations, mobilization initiatives and Centraide
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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 | 0.066 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.012 |
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".