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Record W6925209088 · doi:10.17605/osf.io/7b8sy

Uses of broad consent among diverse populations: A scoping review protocol

2024· other· en· W6925209088 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsInformed consentProtocol (science)Broad spectrumEthical issuesCultural diversityResearch ethics

Abstract

fetched live from OpenAlex

The TCPS-2 does not have guidelines for broad consent that include cultural considerations that may be applicable to the priority populations identified by the psychology training clinic. Thus, the objective of the present scoping review is to create a comprehensive list of any research involving the two main concepts under study. The purpose of this scoping review is to examine the use of broad consent among vulnerable populations in Canada, with the intention to identify cultural considerations that may need to be incorporated in the future implementation of broad consent in research. There are two research questions: (1) Have there been any documentations of the use of broad consent among diverse populations in Canada? (2) What are the cultural considerations that need to be incorporated in the implementation of broad consent for future research?

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)0.308
metaresearch head score (Gemma)0.269
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.308
Threshold uncertainty score0.853

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3080.269
Meta-epidemiology (narrow)0.0040.007
Meta-epidemiology (broad)0.0090.009
Bibliometrics0.0210.018
Science and technology studies0.0080.010
Scholarly communication0.0120.011
Open science0.0060.010
Research integrity0.0130.011
Insufficient payload (model declined to judge)0.0550.018

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 head0.209
GPT teacher head0.550
Teacher spread0.341 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2024
Admission routes1
Has abstractyes

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