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Record W2008047256 · doi:10.3917/spub.092.0183

Le développement des communautés au Québec : la part de l'intelligence collective

2009· article· fr· W2008047256 on OpenAlex
Réal Boisvert, Claire Milette

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSanté Publique · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsCollective intelligencePolitical sciencePlan (archaeology)Public relationsOrder (exchange)WelfareSociologyPublic administrationKnowledge managementBusinessGeographyComputer scienceLaw

Abstract

fetched live from OpenAlex

This article introduces guidelines and certain applications of a national plan and mechanism currently deployed in several regions of Quebec for advancing knowledge on community development. This scheme relies upon the collective intelligence of communities and supports the efforts of various stakeholders in order to improve population living conditions, health and welfare. It primarily distinguishes itself by granting equal importance to quantitative data collected from administrative files and to qualitative data acquired by acknowledging and processing perceptions and observations which arise from actors working in community development. These data are used to support the preparation and planning of interventions implemented according to the socio-economic and socio-health situation of the communities and their potential for development.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.339
Teacher spread0.299 · 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