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Record W1995348278 · doi:10.1017/s0963180108080055

Genetic Justice Must Track Genetic Complexity

2007· article· en· W1995348278 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge Quarterly of Healthcare Ethics · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEconomic JusticeHeredityNatural (archaeology)PoliticsNatural experimentSociologyTrack (disk drive)PsychologyPolitical scienceLawComputer scienceMedicineBiologyGenetics

Abstract

fetched live from OpenAlex

Many different factors influence our health prospects. The food we consume, the lifestyle we live (e.g., sedentary or active), our economic prospects, our love prospects, our gender, our age, and our education all influence our expected lifetime acquisition of what John Rawls calls the "natural primary goods" (e.g., health, vigor, imagination, and intelligence). Our well-being is also influenced by the natural endowments we inherit from our parents. All people have two copies of most genes, one from their mother and one from their father. Genes are the fundamental physical and functional unit of heredity; they "specify the proteins that form the units of which homoeostatic devices are composed."Earlier versions of this paper were presented to the Department of Philosophy at the University of Waterloo, the James Martin Advanced Research Seminar at Oxford University, and the Department of Politics at Manchester University. I am grateful for the helpful feedback that I received on those occasions.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.372
Teacher spread0.299 · 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