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Record W4409812932 · doi:10.5334/aogh.4609

The Impact of Medical Waste on Indigenous Communities in Balochistan Pakistan: Sustainable Solutions in Reducing Inequality and Improving Resilience in Communities

2025· article· en· W4409812932 on OpenAlex
Shakir Ullah, Usman Khan, Qasim Jan, Taher Saifuddin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Global Health · 2025
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsThe Scarborough Hospital
Fundersnot available
KeywordsIndigenousResilience (materials science)InequalityGeographySocioeconomicsEnvironmental planningEconomic growthDevelopment economicsSociologyEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

Aim: The study investigated the adverse impact of medical waste on Indigenous communities and explored sustainable solutions to reduce inequality and enhance resilience. Methods: We adopted a qualitative thematic analysis from primary data collected from 176 respondents. Data were collected through focus groups and interviews. Results: In the research, we examined the interconnected themes challenging medical waste management practices in Pakistan, such as poor disposal practices, health and environmental hazards of poor medical waste management through disease transmission and infections, and soil and water contamination. Socioeconomic disparities and inequality were also identified, resulting in economic burdens on vulnerable groups—the theme of which was Indigenous communities disadvantaged through health risks and vulnerabilities and disproportionate impact on health and well‑being. Themes further highlight government efforts, suggested regulatory and policy reforms, capacity building, and awareness. Recommendations: We developed three significant recommendations for sustainable solutions to reducing inequality and improving community resilience. The first is community empowerment and awareness, emphasizing the need to educate community members, healthcare professionals, and waste handlers about the risks of improper medical waste disposal. The second is strengthening infrastructure and collaboration, highlighting the urgent need to establish proper waste collection and segregation infrastructure. Collaboration among healthcare facilities, waste management agencies, government bodies, and community leaders is instrumental in designing comprehensive solutions that meet the unique needs of Indigenous communities. The third one is policy enhancement and enforcement, suggesting the importance of policy revisions and rigorous enforcement mechanisms. The study advocates for policies that reflect current challenges and encourage innovative approaches to medical waste management.

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.

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)0.004
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 score0.446
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.053
GPT teacher head0.434
Teacher spread0.380 · 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