Social participation in the definition of budgetary instruments
Bibliographic record
Abstract
Purpose The participation of society is a valuable aspect of the governability of cities, for it strengthens the citizens’ collaborative component. Such participation, which is seen as social, is considered an essential element for the design of a smart city. This study aims to identify the factors that contribute to social participation in the definition of budgetary instruments’ planning. Design/methodology/approach Concerning the methodological instruments, this study is characterised by a quantitative and descriptive approach and uses a multivariate data analysis with a sample of 235 respondents. Findings The study’s findings identified a framework that portrays elements that collaborate with the social participation in the definition of the public administration’s budgetary instruments, which are considered as elements that are able to develop the role of the popular participation and are characterised by the definition of a smart city by enabling more assertiveness in society’s needs. Practical implications Identification of a framework that brings out elements that are able to develop the popular participation in the definition of budgetary instruments. Then, one scale of elements that contribute to social participation in the definition of the public administration’s budgetary instruments theoretically represented and statistically validated, thus contributing to the continuity of studies on social participation. Social implications Through studies on social participation in budgetary planning, it is possible to guarantee a better allocation of public resources through intelligent governability. Originality/value The research can bring theoretical elements about social participation in the definition of budget instruments for a statistical convergence through the perception of the sample.
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 | 0.024 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".