The AccèsLogis Québec Program: 15 years of Partnership Between the State and the Social Economy
Bibliographic record
Abstract
Over the past 15 years, the Quebec government’s public policy on social and community housing has been based mainly on the AccèsLogis program. Under this program, some 23,000 new social housing units have been developed. While the program’s regulations and funding are governed by the public sector (primarily provincial, secondarily federal), its development and implementation rely heavily on the participation of social and solidarity economy (SSE) stakeholders, and particularly on the input of housing Non Profit Organizations (NPOs) and co-operatives. In other words, SSE stakeholders play a significant role in program implementation (co-production) and in its definition and design (co-construction), to use a distinction favoured in this paper’s conceptual framework (Vaillancourt, 2009). This appraisal of the AccèsLogis program is based on research that was mostly done in partnerships since 1995. Our paper is divided into two parts: first, we present the context in which the AccèsLogis program emerged, along with its main characteristics; then we show that the program represents a social innovation in which SSE stakeholders make a major contribution while participating not only in the implementation of the program (co-production), but also in defining its architecture (co-construction).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".