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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.229 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".