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Record W4210691771 · doi:10.1152/advan.00021.2021

Change the medium, change the message: creativity is key to battle misinformation

2022· editorial· en· W4210691771 on OpenAlexaff
Kayla A. Benjamin, Sarah McLean

Bibliographic record

VenueAJP Advances in Physiology Education · 2022
Typeeditorial
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsScientific literacyScience communicationPseudoscienceMisinformationScience educationJargonMainstreamSociologyInformal educationMedia literacyPublic awareness of scienceNext Generation Science StandardsInformal learningContext (archaeology)Public relationsPedagogyPolitical scienceHigher educationMedicineLaw

Abstract

fetched live from OpenAlex

Marshall McLuhan’s groundbreaking work regarding the role of context and medium in communication is very relevant today. By limiting the medium of science communication to dense, jargon-rich academic journals, we restrict the impact of discovery to the scientific community. We are also allowing the propagation of misinformation, as the nonexpert is forced to resource unreliable media to answer their scientific queries. To compete with pseudoscience, we need to improve science literacy and make science accessible through the same media on which pseudoscience thrives. As scientists and educators, we believe it is our responsibility to reconceptualize science literacy as a lifelong process and take greater accountability over the future of science communication. We hypothesize that increasing the accessibility of scientific literature to the public through adopting mainstream media forms and increasing access to informal science education (ISE) opportunities will decrease the proliferation of pseudoscience. To accomplish this, we propose eight recommendations housed under three action areas: 1) modify undergraduate science education by increasing opportunities for informal science communication, 2) increase accessibility to informal science education, and 3) bridge the gap between formal and informal science learning opportunities.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.204
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.379
Teacher spread0.347 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations6
Published2022
Admission routes1
Has abstractyes

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