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Record W4413501719 · doi:10.1093/heapro/daaf139

Learning from community narratives about the COVID-19 pandemic in Papua New Guinea

2025· article· en· W4413501719 on OpenAlexaboutno aff
Elisabeth Schuele, Odette Toloube, Karika Anea, Rhonda Wohemani, Colin MacDougall, Joseph G. Giduthuri

Bibliographic record

VenueHealth Promotion International · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsMisinformationSociologyPublic healthThematic analysisPandemicPolitical scienceMedicinePsychologyQualitative researchSocial scienceCoronavirus disease 2019 (COVID-19)Nursing

Abstract

fetched live from OpenAlex

In this paper we use constructivism to explore community members' accounts of how socio-cultural and behavioral factors provided meaning to the COVID-19 pandemic in Papua New Guinea, adherence to "niupela pasin" (new normal), and vaccination acceptance. We purposively selected 50 participants including community members, leaders, and church representatives for semi-structured interviews from urban and rural areas of Madang and Eastern Highlands Provinces. Data were analyzed using inductive thematic analysis. The findings showed how people applied risk prevention strategies and actively sought localized solutions to deal with the pandemic. The pandemic also disrupted socio-cultural norms, such as communal gatherings, care for the sick, and attending funerals, leading to distress and interruptions of interpersonal relationships and extended family structures. Economic hardship, particularly during lockdowns, disproportionately affected those people from lower socioeconomic levels. Strong Christian faith and prayer played a key role in either adhering to "niupela pasin" and COVID-19 vaccine acceptance or rejection of the vaccine. Conspiracy theories and misinformation often propagated through social media, fueled fears and doubts about vaccine efficacy. By articulating and understanding these culturally informed findings, the paper demonstrates how people undertook ordinary theorizing about their worlds to contextualize, modify, or significantly change the policies and strategies developed by experts using conventional science. Preparation for future pandemics can be enhanced by adding to public health policies and guidelines community perspectives and health promotion principles from the Ottawa Charter for Health Promotion.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.146
GPT teacher head0.451
Teacher spread0.305 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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