Toward a model of the municipal evidence-based decision process in the strategic digital city context
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
Technological and connected modern cities demand effective decisions by managers that are aligned with citizens demands. The strategic digital city that comprises strategies, information, services, and information technology resources can provide the necessary context so that decisions based on evidence are made possible at the municipal level of management. The objective of this study is to propose a municipal decision process model in the context of the strategic digital city. The research methodology employed was qualitative and applied to circumstantial theoretical reality, emphasizing exploratory and descriptive methods aided by bibliographic and documentary survey along with the non-participatory observation of the variables that make up the model. Similar models were identified and analyzed. The municipal decision process in the context of the strategic digital city was built from three constructs: decision, evidence, and strategic digital city. These constructs are interconnected by their thirteen variables, which are related to the conceptual base of the model developed. The conclusion reinforces the importance of using evidence to support the decision process, making it one of the strategic elements for digital cities aiming at improving their citizens quality of life.
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 | 0.000 | 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 | 0.001 |
| 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