Bibliographic record
Abstract
This paper is a part of a research of on-line community deliberation with the aim to explore the potential of cyberspace in further development of community deliberative engagement. That is to be the introductory preliminary work for a planned research of exploring possibilities of community deliberative engagement for the debates and decisions dealing with the issues related to climate change. The project which at this stage involves Australia, US, Canada (where some of the field work is already being done), UK (where the preparations are on the way) and Croatia (where, so far, the general endorsement has been initially stated by the University of Dubrovnik as the partner in the projects) will also include research and in some cases experiments with on-line deliberation in the area of climate change. The general idea is to use comparative case studies and experimental design to determine what would be methods, processes and connections to policy processes, and what type of information are needed in the deliberation process. The underlying driver for this research is the belief of the social scientists involved that well designed citizen’s deliberation can shift the politics of climate change.
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 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 | 0.033 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".