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Record W2147240853 · doi:10.1525/maq.2007.21.3.256

Susceptibility Genes and the Question of Embodied Identity

2007· article· en· W2147240853 on OpenAlexafffund
Margaret Lock, Julia Freeman, Gillian Chilibeck, Briony Beveridge, Miriam Padolsky

Bibliographic record

VenueMedical Anthropology Quarterly · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsMcGill University
FundersNational Human Genome Research InstituteNational Institute on AgingNational Center for Research ResourcesSocial Sciences and Humanities Research Council of Canada
KeywordsEmbodied cognitionDiseaseCausationIdentity (music)Genetic testingPsychologyGeneticsEpistemologyMedicineBiologyPhilosophyAestheticsPathology

Abstract

fetched live from OpenAlex

Drawing on an assumption of the co-construction of the material and the social, late-onset Alzheimer's disease (AD) is used as an illustrative example to assess claims for an emergent figure of the "individual genetically at risk." Current medical understanding of the genetics of AD is discussed, followed by a summary of media and AD society materials that reveal an absence of gene hype in connection with this disease. Excerpts from interviews with first-degree relatives of patients diagnosed with AD follow. Interviewees hold complex theories of causation. After genetic testing they exhibit few if any subjective changes in embodied identity or lifestyle. Family history is regarded by interviewees as a better indicator of future disease than is genetic testing. We argue that, even when molecular genetics are better understood, predictions about complex disease based on genotyping will be fraught with uncertainty, making problematic the concept of individuals as genetically at risk when applied to late-onset complex disease.

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)0.006
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.064
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.309
Teacher spread0.302 · 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

Citations77
Published2007
Admission routes2
Has abstractyes

Explore more

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