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Record W4411375190 · doi:10.18280/ijsdp.200526

Community-Based Knowledge Systems and Energy-Aware Empowerment in Breast Cancer Prevention: A Case Study from Bontang, Indonesia

2025· article· en· W4411375190 on OpenAlexvenueno aff
Erni Asneli Asbi, Ramadhan Harahap, Zulfendri Zulfendri, Harmona Daulay

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentBreast cancerEnergy (signal processing)Environmental planningMedicineCancerBusinessGeographyEconomic growthEconomicsInternal medicine

Abstract

fetched live from OpenAlex

This study presents a quantitative analysis of breast cancer awareness in relation to energy and ICT infrastructure in Bontang City, Indonesia.Using a structured survey and statistical modeling, the research evaluates how access to electricity, mobile internet, and communication tools affects health knowledge dissemination.A sample of 23 participants including health cadres, survivors, and community members was assessed using Partial Least Squares Structural Equation Modeling (PLS-SEM), Chi-Square tests, and Pearson correlation to determine key factors influencing preventive behavior.Results reveal that infrastructure access, awareness engagement, and source credibility significantly enhance breast cancer knowledge dissemination, while social resistance and misinformation pose substantial barriers.The findings underscore the importance of integrated energy and health communication strategies, suggesting that reliable infrastructure is essential not only for physical well-being but also for supporting preventive healthcare education.This research contributes a replicable quantitative framework to support community-based health planning in energy-constrained regions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.346
Teacher spread0.322 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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