Brazilian protocol to the certification of Cities in the Global Network of Cities and Communities Friendly to the Elderly of the World Health Organization (WHO)
Bibliographic record
Abstract
Population aging is a progressive phenomenon, especially in developing countries. Given this scenario, international organizations have drawn attention to the advancement of aging worldwide. For this, these organizations have promoted fundamental actions encouraging the creation of friendly environments for the elderly, among these actions, the Age-friendly cities and communities and the Global Network for Age-friendly Cities and Communities stand out. In 2022 there were 1,445 cities included in the Global Network of the World Health Organization, of these, 849 cities are located in the Americas, among which 31 are Brazilian. For the certification of cities in the aforementioned Network, it is necessary to meet several criteria established by the World Health Organization (WHO), through recommended protocols. However, with the experience acquired in monitoring the certification of twenty-three cities in Paraná, it was possible to perceive the lack of a national protocol in Brazil, since the certification process that took place in Brazilian cities was supported by international protocols. Due to this scenario, the problem of this thesis originated, namely: Brazilian experiences, based on international protocols and adapted to the national context, could support the creation of a Brazilian protocol for the certification process of cities or towns in the Global Cities and Communities Network WHO Age-friendly? And what would your contributions be? With the general objective of proposing a Brazilian Protocol model for the process of certification of cities and communities in the WHO Global Network for Age-friendly Cities and Communities, based on Brazilian experiences, contributing to facilitate the process, as well as helping managers, municipal planners, researchers and civil society regarding the expansion of friendly environments for the elderly and other ages. The methodology chosen, considering the characteristics of the study, was the qualitative approach, consisting of bibliographical and documentary research, participant research and semi-structured interviews. Regarding to the interviewees, six researchers who participated in the certification of eighteen Brazilian cities were interviewed, along with the WHO Global Network for age-friendly Cities and Communities. In this sense, the results showed that the certification protocols used are based on documents, such as: Vancouver Protocol (WHO, 2006), Global Guide for Age-Friendly Cities (WHO, 2007) and WHO Global Network of Cities and Age-Friendly Communities (WHO, 2010). The awareness stage, listening to the elderly population, as well as the construction of the Municipal Action Plan for the Elderly, were fundamental in the process of certification of Brazilian cities. Contributions from Brazilian experiences supported the creation of a Brazilian protocol model for the certification process of cities in the WHO Global Network for age-friendly Cities and Communities.
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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 | 0.046 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".