Decision Model for Policy Makers in the Context of Citizens Engagement
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
Citizens’ engagement is considered as one of the important dimensions for the development of smart cities since, in the vision of a city of the future (smart city), citizens will be more and more involved in the decision-making process of different issues related to the development of a city. In this context, policy makers face a decision problem where they have to integrate a new dimension, which is the voice of the citizens’ decision. This article proposes a tool based on multicriteria decision making methods to provide decision makers with the best alternative(s) that are based on citizens’ opinions. In order to tackle the potential interdependencies between criteria and also between alternatives in the selection process, we apply a hybrid model integrating the analytical network process and an extended version of technique for order performance by similarity to ideal solution to support group decision-making. The proposed model is applied in the context of participatory budgeting (PB) where citizens decide on the projects in which the money can be invested. This process is complex since it encompasses multiple interdependent criteria that may be conflicting with each other and that are used to take decisions. To illustrate our approach, we will apply the proposed technique for the case study of La Marsa, a city in the north of the capital Tunis (Tunisia) that adopted, since 2014, a PB strategy in which citizens proposed alternatives on how an amount of money can be used to lighten specific streets in the city.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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