MétaCan
Menu
← Back to cohort
Record W4395460807 · doi:10.1515/9782763734668

Parlons bioéthique

2017· book· fr· W4395460807 on OpenAlexaboutno aff
Margarita Boladeras, Anne Fagot-Largeault, Jean-Yves Goffi, Gilbert Hottois, Jean‐Noël Missa, Marie‐Hélène Parizeau

Bibliographic record

Venuenot available
Typebook
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

Ce livre présente cinq entretiens avec des philosophes pionniers dans le champ de la bioéthique francophone, Anne Fagot-Largeault et Jean-Yves Goffi (France), Gilbert Hottois et Jean-Noël Missa (Belgique) et Marie-Hélène Parizeau (Québec), cinq personnalités de renom, connues pour leur trajectoire exceptionnelle. Les entretiens menés avec ces auteurs au sujet de leurs oeuvres, de leurs expériences dans des comités de bioéthique et des différents débats soulevés ces dernières années nous permettent de connaître leur travail, mais aussi de faire une incursion dans le développement fulgurant de la bio-médecine et des biotechnologies des cinquante dernières années. Les conséquences de ces applications, les problèmes éthiques générés, les jugements favorables et défavorables à l’égard des changements sociaux qui se sont produits et le bouleversement d’idées qui s’en est suivi, sont autant d’aspects abordés dans ces entretiens. L’utilisation du langage courant exige un effort de synthèse important; aussi ces entretiens sous la forme d’une conversation, offrent-ils au lecteur une large vision panoramique, rigoureuse et concise de l’évolution de la bioéthique francophone.

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)0.007
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.013
Scholarly communication0.0110.007
Open science0.0020.005
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0440.013

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 head0.138
GPT teacher head0.468
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
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicHealth, Medicine and Society→French-language works237,207→