Implementasi Kawasan tanpa Rokok dalam Upaya Promosi Kesehatan di Universitas Airlangga
Bibliographic record
Abstract
Smoking is a behavior that is widely found in all levels of society, including at universities. In an effort to improve health status and create a Healthy Campus, Universitas Airlangga inaugurated a Smoking Free Area. This study aims to examine smoking behavior and analyze the implementation of No-Smoking Areas (KTR) at Airlangga University based on the Ottawa Charter health promotion strategy. This research is a case study using a descriptive qualitative approach with several data collections, namely interviews, observation and literature study. If reviewed based on the Ottawa Charter, the implementation of KTR at Universitas Airlangga has been going well. The KTR program at Airlangga University already has a health-oriented public policy, namely Peraturan Rektor Universitas Airlangga Nomor 13 Tahun 2023 Tentang Pedoman Kawasan Tanpa Rokok di Lingkungan Universitas Airlangga. KTR has succeeded in establishing a supportive environment, marked by the prohibition of smoking signs posted at the campus gate and every building. KTR also strengthens community action through the KTR task force from each faculty. To develop personal skills, KTR is also balanced with education and outreach to the task force and the entire academic community. The rearrangement of health services has also been carried out, in which health service facilities and related units have also improved and added smoking-related services to create a Kawasan Tanpa Rokok at Airlangga University. Kawasan Tanpa Rokok is a form of health promotion in an effort to create a Healthy Campus at Airlangga University. The rector's regulation has been promulgated to support its implementation. The results of observations reviewed based on the Ottawa Charter show that there is a link between the implementation of KTR and the available infrastructure, human resources, and policies set at Airlangga University.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".