Fostering cooperative community behavior with IT tools: the influence of a designed deliberative space on efforts to address collective challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How to encourage cooperative behavior and facilitate collaboration amongst diverse stakeholders to achieve collective goals remains a longstanding question in realizing a community’s capacity for local problem solving. Governments have increasingly adopted inclusive processes to engage non-state actors, and especially active engagement of citizens and communities in solving local policy challenges. Yet, the success of this inclusive approach depends on whether and to what extent all involved individuals, interest groups, communities, and government agencies can collectively deliberate and work together. We conducted experiments to explore the potential of IT-facilitated communication environment designed for deliberation activities to address collective challenges. Our unique experimental site for this research is a designed deliberation space that can seat up to 30 participants surrounded by the 260-degree seven-screen communal display. Our study shows that when people deliberate on a local community challenge under the environment with a communal display, they show more cooperative behavior in a social dilemma scenario than those who deliberate on the same challenge presented on individual displays. This study highlights the potential of technology’s influence on public deliberation in such a way as to promoting collective behavior.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it