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Record W2004942351 · doi:10.1111/hex.12122

Community engagement with genetics: public perceptions and expectations about genetics research

2013· article· en· W2004942351 on OpenAlexafffundabout
Holly Etchegary, Jane Green, Patrick S. Parfrey, Catherine Street, Daryl Pullman

Bibliographic record

VenueHealth Expectations · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMemorial University of Newfoundland
FundersAtlantic Canada Opportunities AgencyGenome Canada
KeywordsBiobankPacePublic engagementPublic healthGenomicsVariety (cybernetics)PerceptionPublic relationsPsychologyMedicinePolitical scienceGeneticsBiologyNursingComputer scienceGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge of molecular biology and genomics continues to expand rapidly, promising numerous opportunities for improving health. However, a key aspect of the success of genomic medicine is related to public understanding and acceptance. DESIGN: Using community consultations and an online survey, we explored public attitudes and expectations about genomics research. RESULTS: Thirty-three members of the general public in Newfoundland, Canada, took part in the community sessions, while 1024 Atlantic Canadians completed the online survey. Overall, many participants noted they lacked knowledge about genetics and associated research and took the opportunity to ask numerous questions throughout sessions. Participants were largely hopeful about genomics research in its capacity to improve health, not only for current residents, but also for future generations. However, they did not accept such research uncritically, and a variety of complex issues and questions arose during the community consultations and were reflected in survey responses. DISCUSSION: With the proliferation of biobanks and the rapid pace of discoveries in genomics research, public support will be crucial to realize health improvements. If researchers can engage the public in regular, transparent dialogue, this two-way communication could allow greater understanding of the research process and the design of efficient and effective genetic health services, informed by the public that will use them.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.122
GPT teacher head0.402
Teacher spread0.281 · 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.

Study designQualitative
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

Citations43
Published2013
Admission routes3
Has abstractyes

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