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Record W2883572885 · doi:10.1007/s00439-018-1903-2

China: concurring regulation of cross-border genomic data sharing for statist control and individual protection

2018· review· en· W2883572885 on OpenAlex
Yongxi Chen, Lingqiao Song

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHuman Genetics · 2018
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMcGill University
FundersMcGill University
KeywordsBiologyChinaCorporate governanceData sharingGovernment (linguistics)Political scienceBusinessLaw

Abstract

fetched live from OpenAlex

This paper reviews the major legal instruments and self-regulations that bear heavily on the cross-border sharing of genomic data in China. It first maps out three overlapping frameworks on genomic data and analyzes their underpinning policy goals. Subsequent sections examine the regulatory approaches with respect to five aspects of responsible use and sharing of genomic data, namely, consent, privacy, security, compatible processing, and oversight. It argues that substantial centralised control exerted by the state is, and would probably remain, the dominant feature of genomic data governance in China, though concerns of individual protection are gaining momentum. Rather than revolving around a simplistic antinomy between privacy preservation and open science, the regulatory landscape is mainly shaped by the tension between government desires for national security, state competitiveness, and public health benefits.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.891
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.679
GPT teacher head0.657
Teacher spread0.021 · 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