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Record W645380310 · doi:10.1017/cbo9780511621765

Living and Working with the New Medical Technologies

2000· book· en· W645380310 on OpenAlexaff
Margaret Lock, Alberto Cambrosio, Hans‐Jörg Rheinberger, Paul Rabinow, Ilana Löwy, Annemarie Mol, Peter Keating, Allan Young, Patricia A. Kaufert, Rayna Rapp, Joseph Dumit, Veena Das

Bibliographic record

VenueCambridge University Press eBooks · 2000
Typebook
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsMcGill University
Fundersnot available
KeywordsEthnographyFace (sociological concept)Reading (process)Product (mathematics)Focus (optics)Emerging technologiesSociologyEngineering ethicsEpistemologyPublic relationsPolitical scienceSocial scienceEngineeringComputer scienceAnthropologyLawPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

This stimulating collection of essays is the product of face-to-face dialogues among anthropologists, sociologists, and philosopher-historians, all of whom focus their attention on the newly created biomedical technologies and their application in practice. Drawing on ethnographic and historical case studies, the authors show how biomedical technologies are produced through the agencies of tools and techniques, scientists and doctors, funding bodies, patients, clients, and the public. Despite shared concerns, these essays reveal that the authors have achieved no consensus about the objectives of their research, and the deep epistemological divides clearly remain - making for provocative reading.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.996
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.023
Scholarly communication0.0090.011
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.003

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 head0.009
GPT teacher head0.182
Teacher spread0.173 · 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.

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

Citations200
Published2000
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicRace, Genetics, and SocietyFrench-language works237,207