MétaCan
Menu
Back to cohort
Record W2591821213 · doi:10.1139/facets-2016-0015

Communicating science: Sending the right message to the right audience

2016· article· en· W2591821213 on OpenAlex
Matthew Wilson, Tonya L. Ramey, Michael Donaldson, Ryan R. Germain, Elizabeth K. Perkin

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueFACETS · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsCarleton UniversityUniversity of British Columbia
Fundersnot available
KeywordsContext (archaeology)Identity (music)Public relationsInformation flowInternet privacyScience communicationPublic trustPsychologyPolitical scienceComputer scienceScience educationPedagogy

Abstract

fetched live from OpenAlex

For science communication to be effective, scientists must understand which sources of information their target audiences most frequently use and trust. We surveyed academic and non-academic scientists, natural resource managers, policymakers, students, and the general public about how they access, trust, and communicate scientific information. We found trust and use of information sources was related to participant age and group identity, but all groups had high levels of use and trust of personal experience and colleagues. Academic journals were the most trusted source by all groups, and social media the least trusted by most groups. The level of communication between target groups was not always bilateral, with the public generally perceiving their interaction with all other groups as low. These results provide remarkable insight into the flow of scientific information. We present these findings in the context of facilitating information flow between scientists and other stakeholders of scientific information.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.281
GPT teacher head0.453
Teacher spread0.172 · 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