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Record W3006538489 · doi:10.1038/s41597-020-0388-8

The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries

2020· article· en· W3006538489 on OpenAlexaff
Mark T. van Wijk, James Hammond, Léo Gorman, S.N. Adams, Augustine A. Ayantunde, David Baines, Adrian Bolliger, Caroline K. Bosire, Pietro Carpena, Sabrina Chesterman, Amon Chinyophiro, Happy Daudi, Paul Dontsop, Sabine Douxchamps, Willy Desire Emera, Simon Fraval, Steven J. Fonte, Lyda Hok, Henry Kiara, Esther Kihoro, L. Korir, Christine Lamanna, Chau Thi Minh Long, Godfrey Manyawu, Zia Mehrabi, Dejene K. Mengistu, Leida Mercado, Katherin Meza, Jacob Mutemi, Mary Ngendo, Paulin Njingulula, Tim Pagella, Phonepaseuth Phengsavanh, James Rao, Randall S. Ritzema, Todd S. Rosenstock, Tom Skirrow, Jonathan Steinke, Clare Stirling, José Gabriel Suchini, Nils Teufel, Peter S. Thorne, Steven J. Vanek, Jacob van Etten, Bernard Vanlauwe, Jannike Wichern, Viviane Yameogo

Bibliographic record

VenueScientific Data · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of British Columbia
FundersConsortium of International Agricultural Research CentersUnited States Agency for International Development
KeywordsFood securityHousehold incomeSurvey data collectionLivestockAgricultureWelfareProductivityPovertyIndex (typography)Agricultural economicsGeographyProduction (economics)Scale (ratio)Agricultural productivityBusinessSocioeconomicsEconomicsEconomic growthStatistics

Abstract

fetched live from OpenAlex

The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 758 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators such as the Probability of Poverty Index, the Household Food Insecurity Access Scale, and household dietary diversity. These variables are used to quantify more than 40 different indicators on farm and household characteristics, welfare, productivity, and economic performance. Between 2015 and the beginning of 2018, the survey instrument was applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here include the raw survey response data, the indicator calculation code, and the resulting indicator values. These data can be used to quantify on- and off-farm pathways to food security, diverse diets, and changes in poverty for rural smallholder farm households.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0060.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.485
GPT teacher head0.452
Teacher spread0.034 · 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 designNot applicable
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

Citations44
Published2020
Admission routes1
Has abstractyes

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