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Record W2138221487 · doi:10.1093/jlb/lsu031

Consent in escrow

2014· article· en· W2138221487 on OpenAlexafffund
Kiah I. Van der Loos, Holly Longstaff, Alice Virani, Judy Illes

Bibliographic record

VenueJournal of Law and the Biosciences · 2014
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsNeuroDevNetUniversity of British Columbia
FundersBC Cancer AgencyCanadian Institutes of Health ResearchSimon Fraser UniversityVancouver Coastal Health Research InstituteCanada Research Chairs
KeywordsDistrustEscrowInternet privacyComputer securityInformed consentWindow of opportunityKey escrowPsychologyBusinessActuarial scienceComputer sciencePolitical scienceMedicineLawAlternative medicine

Abstract

fetched live from OpenAlex

Disasters such as flash flooding, mass shootings, and train and airplane accidents involving large numbers of victims produce significant opportunity for research in the biosciences. This opportunity exists in the extreme tails of life events, however, during which decisions about life and death, valuing and foregoing, speed and patience, trust and distrust, are tested simultaneously and abundantly. The press and urgency of these scenarios may also challenge the ability of researchers to comprehensively deliver information about the purposes of a study, risks, benefits, and alternatives. Under these circumstances, we argue that acquiring consent for the immediate use of data that are not time sensitive represents a gap in the protection of human study participants. In response, we offer a two-tiered model of consent that allows for data collected in real-time to be held in escrow until the acute post-disaster window has closed. Such a model not only respects the fundamental tenet of consent in research, but also enables such research to take place in an ethically defensible manner.

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 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)0.009
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.113
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.423
GPT teacher head0.560
Teacher spread0.137 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2014
Admission routes2
Has abstractyes

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