Initial Public Perceptions of Deep Geological and Oceanic Disposal of Carbon Dioxide
Bibliographic record
Abstract
Two studies were conducted to gauge likely public perceptions of proposals to avoid releasing carbon dioxide from power plants to the atmosphere by injecting it into deep geological formations or the deep ocean. Following a modified version of the mental model interview method, Study 1 involved face-to-face interviews with 18 nontechnical respondents. Respondents shared their beliefs after receiving basic information about the technologies and again after getting specific details. Many interviewees wanted to frame the issue in the broader context of alternative strategies for carbon management, but public understanding of mitigation strategies is limited. The second study, administered to a sample of 126 individuals, involved a closed-form survey that measured the prevalence of general beliefs revealed in study 1 and also assessed the respondent's views of these technologies. Study results suggest that the public may develop misgivings about deep injection of carbon dioxide because it can be seen as temporizing and perhaps creating future problems. Ocean injection was seen as more problematic than geological injection. An approach to public communication and regulation that is open and respectful of public concerns is likely to be a prerequisite to the successful adoption of this technology.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".