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Record W2128332960 · doi:10.7202/045365ar

La United Kingdom Stem Cell Bank

2011· article· fr· W2128332960 on OpenAlexaffvenue
Virginie Tournay, Marie‐Odile Ott, Dörte Bemme, Christelle Routelous

Bibliographic record

VenueSociologie et sociétés · 2011
Typearticle
Languagefr
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’objectif de cette contribution est d’étudier le lien entre l’organisation matérielle confinée de recherches émergentes autour du vivant, leur consolidation disciplinaire et le déploiement d’espérances collectives à grande échelle. Le cas d’étude est la United Kingdom Stem Cell Bank, décrite comme une architecture performative dotée d’une efficacité organisationnelle et jouant un rôle clé dans la gouvernance internationale de la manipulation des cellules souches embryonnaires humaines. L’enjeu consiste à montrer que la structuration de cet espace confiné et stérile, nécessaire au maintien des cellules souches embryonnaires humaines, est également celle d’un espace de coopérations multilatérales et internationalisées autour de ces produits biologiques. Pour étudier cette tension scalaire, la différenciation institutionnelle de la UK Stem Cell Bank est appréhendée comme une catégorie de mouvement d’individus, de produits biologiques et de données les concernant. En intégrant les perspectives récemment développées autour des policy transfer studies, cette contribution met l’accent sur le mouvement régulier, répété et centralisé de collecte de cellules d’origine humaine vers cet espace confiné, ainsi que sur les procédures d’étalonnage et d’enregistrement des données pour expliquer le succès de ce modèle local à grande échelle.

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)0.003
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.186
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1860.114

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 head0.428
GPT teacher head0.427
Teacher spread0.001 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

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