Collaborative Decision Making in Urban Regeneration: A Complex Adaptive Systems Perspective
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
ABSTRACT In this paper we examine the processes and participants in urban regeneration with a view to identifying the nature of collaborative decision making in a particular policy arena. Recognizing that the environment in which public managers operate is a complex nexus of agency, structure, environment, and feedback processes, we apply a complex adaptive systems (CAS) framework comprised of agents, rules, outcomes, decision factors, and processes within the public policy arena—in this case urban regeneration in Ireland—in order to explore collaborative decision making in the public domain. The CAS framework draws particular attention to self-organizing features of the system under study and to the emergence of agents, order (“rules”), and outcomes. Using this framework, we found that three of the six urban regeneration projects (“systems”) in our study featured the emergence of project specific agents as important facilitators of collaborative decision making and as key contributors to the expansion of system scope.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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