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Record W3024781415 · doi:10.5539/gjhs.v12n7p72

Health Status of Widows as a Correlate of Their Participation in Community Development Projects in Nsukka, Enugu State, Nigeria

2020· article· en· W3024781415 on OpenAlexvenueno aff
Matthias U. Agboeze, Ruphina U. Nwachukwu, Michael O. Ugwueze, Maryrose N. Agboeze

Bibliographic record

VenueGlobal Journal of Health Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMalariaEnvironmental healthMedicineCommunity participationTraditional medicineGerontologySocioeconomicsSociologyImmunology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study seeks to examine the health status of widows and investigate its effect on their participation in community development projects. METHODS: A cross-sectional study was conducted on the widows and non-widows in six communities out of the 18 communities in Nsukka local government area of Enugu state, Nigeria from 15 January to 29 March 2019. The respondents were tested clinically based on the following health indices; blood pressure, blood sugar level, malaria parasite and typhoid. The widows were also asked the extent to which their health conditions affect their participation in community development projects. RESULTS: The mean blood pressure level of the widows is 160.2100.4Mm/Hg while their mean blood sugar level is 129.8 Mg/dl. 55% of the widows tested positive to typhoid while another 53% tested positive to malaria parasite. Majority (72%) of the widows revealed that health condition such as poor eye sight; arthritis; rheumatism; high blood pressure; diabetes; malaria; typhoid; cough and ulcer limit their participation in community development projects. CONCLUSIONS: The widows in Nsukka have a poor health status when compared to the non-widows in the region, which to a great extent, limits their participation in the community development projects available to them. Therefore, there is a very strong correlation between the health status of widows in Nsukka and their participation in the community development projects.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.075
GPT teacher head0.419
Teacher spread0.345 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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