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Record W2971729298 · doi:10.3917/inno.pr2.0066

Innovation en santé conduite par les médecins et infirmières : l’approche du design participatif à l’hôpital

2019· article· fr· W2971729298 on OpenAlex

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.

Bibliographic record

VenueInnovations · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsUniversity of Ottawa
FundersAgence Nationale de la Recherche
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’objectif de cet article est d’explorer la manière dont les professionnels de la santé contribuent à la conception d’une technologie en santé et d’identifier les éléments qui soulignent la pertinence d’une approche de design participatif dans ce contexte. Pour cela, notre réflexion prend appui sur un projet de conception d’une technologie en santé par les médecins et les infirmiers/ières qui a pour but de les aider à gérer les surcharges informationnelle, communicationnelle et cognitive à l’hôpital. Nous proposons dans cet article un retour réflexif sur cette approche de design participatif. Pour ce faire, nous examinerons l’engagement des professionnels dans la production d’une analyse de leur activité clinique et de leurs pratiques informationnelles, le tout participant au développement d’une technologie ( Machine Learning ) qui contribuera à réduire les différentes formes de surcharge qu’ils doivent quotidiennement gérer. Codes JEL : Y800, I190

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.074
GPT teacher head0.370
Teacher spread0.296 · 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