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Record W2982276576 · doi:10.1371/journal.pone.0224039

Strategic science communication as planned behavior: Understanding scientists’ willingness to choose specific tactics

2019· article· en· W2982276576 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsCarleton University
Fundersnot available
KeywordsNormativeTheory of planned behaviorDemographicsStrategic communicationContext (archaeology)Function (biology)PsychologyHealth communicationTerm (time)Behavioural sciencesSocial psychologyApplied psychologyPublic relationsComputer sciencePolitical scienceSociologyControl (management)

Abstract

fetched live from OpenAlex

Strategic science communicators need to select tactics that can help them achieve both their short-term communication objectives and long-term behavioral goals. However, little previous research has sought to develop theory aimed at understanding what makes it more likely that a communicator will prioritize specific communication tactics. The current study aims to advance the development of a theory of strategic science communication as planned behavior based on the Integrated Behavioral Model. It does so in the context of exploring Canadian scientists' self-reported willingness to prioritize six different tactics as a function of attitudinal, normative, and efficacy beliefs. The results suggest that scientists' beliefs about ethicality, norms, response efficacy, and self-efficacy, are all meaningful predictors of willingness to prioritize specific tactics. Differences between scientists in terms of demographics and related variables provide only limited benefit in predicting such willingness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.749
GPT teacher head0.445
Teacher spread0.304 · 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