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Record W2038410162 · doi:10.1080/14636778.2010.484227

Seeing and knowing in twenty-first century genetic medicine: the clinical pedigree as epistemological tool and hybrid risk technique

2010· article· en· W2038410162 on OpenAlexaff
Jessica Polzer, Ann Robertson

Bibliographic record

VenueNew Genetics and Society · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of TorontoWestern University
FundersNational Cancer Institute
KeywordsSubjectivityContext (archaeology)SociologyEpistemologyCorporate governanceRelation (database)CitizenshipPoliticsPolitical scienceComputer scienceBiologyLawPhilosophyManagement

Abstract

fetched live from OpenAlex

This paper explores the clinical pedigree as a risk technique within the context of the predictive genetic testing (PGT) clinic. We situate the PGT clinic as a site of genetic governance in that it is a site both for the production of knowledge about genetic risk and for intervening in the everyday lives of individuals and their families who learn to cultivate their relations with themselves and their biological relatives in relation to genetic risk knowledge. Drawing on literature of the pedigree as socially constructed and on notions of risk governance, we suggest that the pedigree operates as an epistemological tool and risk technique – that is, as a visual device that assists in organizing the social relations of knowledge production and aids in effecting shifts in patient subjectivity in ways that are consistent with neoliberal notions of active citizenship.

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)0.014
metaresearch head score (Gemma)0.010
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0060.110
Scholarly communication0.0090.011
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.300
Teacher spread0.287 · 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 designQualitative
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

Citations4
Published2010
Admission routes1
Has abstractyes

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