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Record W4408671792 · doi:10.1080/23311886.2025.2480727

Mind the gap: questioning the existence of a ‘knowledge deficit’ in conservation social media message evaluation by scientist, science-trained, and general public audience groups

2025· article· en· W4408671792 on OpenAlex
Alina C. Fisher, Sarah Jacobs, Chaseten Remillard

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCogent Social Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsRoyal Roads UniversityUniversity of Victoria
FundersMitacs
KeywordsSocial mediaPsychologySociologyMedia studiesSocial sciencePublic relationsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Conservation communication tends to assume a knowledge gap between scientists and target audiences and focuses more on education rather than invitational forms of communication. Known as the knowledge deficit approach to science communication, this approach assumes a significant gap between the public and science-trained professionals and hopes to overcome that gap through communicating ‘better’ facts. Through the use of focus group data, this study examines whether a knowledge deficit exists between scientist, science-trained, and general public audience groups’ understanding of conservation concepts and evaluation and interpretation of conservation social media messages. We show that a significant knowledge deficit does not exist between these groups, and furthermore show between group overlap on key themes surrounding the presentation of social media messages. Altogether this suggests that adopting other styles of communication may enhance engagement with conservation issues.

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)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0070.011
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.501
GPT teacher head0.494
Teacher spread0.007 · 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