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Record W2169046770 · doi:10.1177/1757975913512164

Les artisans du changement : autour d’un échange plénier

2014· article· fr· W2169046770 on OpenAlexaffabout
Luc Berghmans, Louise Bouchard, Philippe Lorenzo, Michel O’Neill, Louise Potvin

Bibliographic record

VenueGlobal Health Promotion · 2014
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité de MontréalUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

The closing plenary of the colloquium was an occasion for exchange between the four panelists and the participants. The panelists included Luc Berghmans, a doctor and director of the regional health observatory of Hainaut, Belgium; Louise Bouchard, a sociologist and professor in the Sociology and Anthropology Department, University of Ottawa, Canada; Michel O’Neill, a sociologist and professor at the Faculty of Nursing Sciences, Laval University, Quebec City, Canada; and Philippe Lorenzo, director general of IREPS, the regional bureau for health education and promotion of Picardie in Amiens, France. Louise Potvin, who moderated the plenary, provides the summary that follows. During the colloquium, three main questions were debated: 1. At what point should health be placed at the forefront of local actions, if we wish to promote the values of equity? 2. How should actions at the local, regional, national and global levels be organized and articulated? Who are the partners, and what forms of governance need to be put into place? 3. What are the parameters needed in order to define the roles, tasks and competencies of the implementers of local and regional health programs, the architects of change? Each panelist had to respond to two out of the three questions. We report on the answers that panelists gave to these questions. As it is impossible to verify the exactitude of information given by audience members in support of their viewpoints, only the content of the remarks is given, without mentioning the examples that were provided.

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)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.078
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0100.005
Scholarly communication0.0160.008
Open science0.0020.007
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0780.015

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 head0.150
GPT teacher head0.480
Teacher spread0.330 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2014
Admission routes2
Has abstractyes

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