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Record W4221058648 · doi:10.7202/1087202ar

Re-contact Following Withdrawal of Minors from Research

2022· article· en· W4221058648 on OpenAlexafffundvenue
Dimitri Patrinos, Bartha Maria Knoppers, Erika Kleiderman, Noriyeh Rahbari, David P. Laplante, Ashley Wazana

Bibliographic record

VenueCanadian Journal of Bioethics · 2022
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsJewish General HospitalMcGill University
FundersCanadian Institutes of Health Research
KeywordsMinor (academic)Maturity (psychological)Context (archaeology)Informed consentPsychologyParental consentSocial psychologyLawPolitical scienceMedicineDevelopmental psychologyAlternative medicineHistory

Abstract

fetched live from OpenAlex

Re-contacting minors enrolled in research upon their reaching the age of majority or maturity to seek their autonomous consent to continue their participation is considered an ethical requirement. This issue has generally been studied in the context of minors who are actively involved in the research. However, what becomes of this issue when the minor has been withdrawn from the research or has been lost to follow-up? May researchers re-contact the minor at the age of majority or maturity under these circumstances to seek the consent of the minor to re-join the research? In this paper, we explore the ethical permissibility of recontacting minors whose participation in research has ended, once they have reached the age of majority or maturity. In particular, we identify scenarios in which the participation of a minor in a research project may end and discuss factors that can help determine such an ethical permissibility. Finally, we discuss the practical and ethical challenges of re-contact and present re-consent models that may be used by researchers.

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)0.124
metaresearch head score (Gemma)0.287
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1240.287
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0100.006
Scholarly communication0.0070.007
Open science0.0040.012
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0130.006

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 head0.175
GPT teacher head0.438
Teacher spread0.263 · 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

Citations3
Published2022
Admission routes3
Has abstractyes

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Same venueCanadian Journal of BioethicsSame topicEthics and Legal Issues in Pediatric HealthcareFrench-language works237,207