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Record W4200106999 · doi:10.6000/1929-4409.2021.10.179

Behavior Analysis of Legislators in Health Planning in South Sulawesi Province

2021· article· en· W4200106999 on OpenAlexvenueno aff
Indar Indar, Muhammad Alwy Arifin, Nurhayani Nurhayani, Anwar Mallongi

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsTriangulationQualitative researchPublic healthContent analysisPublic relationsIntervention (counseling)PerceptionQualitative analysisBusinessPolitical sciencePsychologyMedicineGeographySociologyNursingSocial science

Abstract

fetched live from OpenAlex

Health is political because its social determinants are easily accepted in political intervention. Therefore, the health system of a region mandates that health development will take place well if it is supported by good and targeted planning. The purpose of this study is to analyze the behavior of legislators in planning health services in South Sulawesi Province. The research was conducted in the DPRD of Makassar City and Bantaeng Regency. This type of research is a qualitative research. Data was collected using in-depth interviews, observation and document review. Data processing was carried out using triangulation and content analysis methods. The results showed that based on indicators of knowledge, attitudes, perceptions and actions of legislators were in the poor category. In addition, it was known that there was an interest from legislators in terms of health planning, but this interest was indirectly in the interest of improving public health status.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.084
GPT teacher head0.377
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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