Bibliographic record
Abstract
Abstract. Geoscience communication, an emerging discipline within the geosciences, faces a scarcity of theoretical grounding despite abundant practical perspectives. This paper addresses this gap by investigating the application of science communication models (deficit, dialogue, participatory) in geoscience communication, specifically in British Columbia, Canada. The overarching aim is to determine if the ‘deficit to dialogue’ shift often discussed in science communication literature is reflected in geoscience communication practice. Using a content analysis approach, data was collected from publicly accessible websites to qualify and quantify how (activities) and why (objectives) geoscience communication practitioners communicate. The activities and objectives were coded based on terms associated with each model that closely aligned with those described by Metcalfe (2019a,b). Findings reveal a persistence of the deficit model in practice (76 % for objectives, 61 % for activities) with limited adoption of dialogue and participatory approaches. This suggests a discrepancy between theoretical advancements in science communication and their application in geoscience contexts. The study highlights disparities in the use of communication models across target audiences, regions, and venues. While communication with K-12 audiences utilizes dialogue-based approaches, participatory activities are underrepresented, particularly in regions with high population densities (e.g. Lowermainland/Sea-to-Sky: 0 % participatory) and areas where geoscience intersects with public interests (e.g. Northern B.C.: 3 % participatory). By shedding light on the current landscape of geoscience communication in British Columbia, this research informs future endeavours in theory development and practice improvement within the broader field of science communication. However, it also acknowledges the need for localized studies to capture the diverse contexts of science communication practices worldwide.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.427 | 0.198 |
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".