Editorial: The shadowlands of science communication in academia — definitions, problems, and possible solutions
Bibliographic record
Abstract
Abstract. Science communication is an important part of research, including in the geosciences, as it can benefit society, science, and make science more publicly accountable. However, much of this work takes place in “shadowlands” that are neither fully seen nor understood. These shadowlands are spaces, aspects, and practices of science communication which are not clearly defined and may be harmful with respect to the science being communicated or for the science communicators themselves. With the increasing expectation in academia that researchers should participate in science communication, there is a need to address some of the major issues that lurk in these shadowlands. Here the editorial team of Geoscience Communication seeks to shine a light on the shadowlands of geoscience communication and suggest some solutions and examples of effective practice. The issues broadly fall under three categories: 1) harmful or unclear objectives; 2) poor quality and lack of rigor; and 3) exploitation of science communicators working within academia. Ameliorating these will require: 1) clarifying objectives and audiences; 2) adequately training science communicators; and 3) giving science communication equivalent recognition to other professional activities. By shining a light on the shadowlands of science communication in academia and proposing potential remedies, our aim is to cultivate a more transparent and responsible landscape for geoscience communication—a transformation that will ultimately benefit the progress of science, the welfare of scientists, and more broadly society at large.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".