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Record W2070971856 · doi:10.3917/rsi.116.0013

Analyse dimensionnelle du concept de biosécurité face aux risques biologiques

2014· article· fr· W2070971856 on OpenAlexaff
Laurence Bernard, Marie Alderson

Bibliographic record

VenueRecherche en soins infirmiers · 2014
Typearticle
Languagefr
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesBIOSPolitical sciencePhilosophyComputer science

Abstract

fetched live from OpenAlex

Ces dernières années avec le renforcement du discours entourant les risques biologiques de nature bioterroriste, le concept de biosécurité s’est construit graduellement. Une analyse dimensionnelle a permis de contextualiser ce concept. Au départ, la biosécurité était essentiellement un terme technique, touchant aux risques de contamination dans les laboratoires ou au niveau agroalimentaire, pour ensuite être utilisée dans le but de protéger la biodiversité face à la dispersion d’organismes génétiquement modifiés (OGM) dans l’environnement. À présent, il est de plus en plus employé pour désigner la prévention et le contrôle des infections même si son utilisation demeure marginale. Néanmoins, la biosécurité peut-être définie comme la sécurité du vivant et dès lors toucher aux dispositifs de sécurité participant au gouvernement des corps et au pouvoir sur la vie. Une approche plus critique incluant les dimensions sociale et politique sous un angle foucaldien est nécessaire pour élargir la portée du concept de biosécurité aux risques biologiques construits.

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)0.013
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.013
Scholarly communication0.0120.010
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.140
GPT teacher head0.423
Teacher spread0.284 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations1
Published2014
Admission routes1
Has abstractyes

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