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Record W2900532433 · doi:10.1016/j.dib.2018.11.063

Data on the demographics, education, health and infrastructure: Wolaita Zone, Ethiopia

2018· article· en· W2900532433 on OpenAlexaff
Logan Cochrane, Yishak Gecho

Bibliographic record

VenueData in Brief · 2018
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsCarleton University
Fundersnot available
KeywordsAgriculturePublic healthGeographyData setContextualizationEconomic growthEnvironmental planningMedicineComputer science

Abstract

fetched live from OpenAlex

This data article presents a comprehensive data set about Wolaita Zone (Ethiopia), and the Woredas / Districts within it. The tables cover administrative, demographic, educational, agricultural, transport, and water aspects of the zone. The majority of the data is from 2013/2014, however, a few tables provide trend data over recent years. The evidence shows rapid population growth, significant educational challenges, limitations of health coverage, disparities of agricultural extension service provision and potable water. The data are otherwise not available to researchers and these data sets enable greater contextualization for any on-going or future research within the zone. The data were provided by the Zonal Administration in 2015, and were part of a research project that was approved by the Ethiopian Public Health Institute and supported by the Regional Health Bureau.

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)0.001
metaresearch head score (Gemma)0.003
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.043
GPT teacher head0.338
Teacher spread0.295 · 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
GenreDataset

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

Citations21
Published2018
Admission routes1
Has abstractyes

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