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Record W7099511803

*LAREPPS-CRISES, **UQAM

2016· article· en· W7099511803 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsPublic sectorContext (archaeology)Public housingResearch programSocial economySocial innovationPublic policySolidarity economy
DOInot available

Abstract

fetched live from OpenAlex

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).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.816
Threshold uncertainty score0.910

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1840.023

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.

Opus teacher head0.074
GPT teacher head0.231
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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Same topicMedical History and InnovationsFrench-language works237,207