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Record W2123524809 · doi:10.3138/jcfs.37.3.399

Maasai Marriage: A comparative study of Kenya and Tanzania

2006· article· en· W2123524809 on OpenAlexvenueno aff
Ernestina Coast

Bibliographic record

VenueJournal of Comparative Family Studies · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsMaasaiTanzaniaKenyaPastoralismPolygynyGeographySocioeconomicsPopulationDemographySociologyLivestockBiologyEcology

Abstract

fetched live from OpenAlex

This study compares and contrast recent and contemporary nuptiality among Maasai men of Kenya and Tanzania, and represents the first cross-national comparable data set on Maasai marriage (n=2,394) (men aged 20 and above). By comparing nuptiality between Kenyan and Tanzanian Maasai, this study examines marriage among the Massai in particular and rural sub-Saharan African populations undergoing social-economic change in general. Maasai men marry later, on average, than the national average in both Kenya and Tanzania, and the age at first marriage appears to be declining. Relative to national levels, polygynous marriages account for a significantly higher proportion of Maasai marriages. Country-level differences in entry into and type of (monogamous or polygynous) marriage are described and explanations sought. The Maasai of Kenya and Tanzania are arguably the best-known pastoralist population in the world, and the current study represents an opportunity to update and review the body of evidence linking pastoralism with polygyny. Linkages between socio-economic divergence and nuptiality are identified, with specific reference to uptake of formal education.

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)0.000
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 score0.160
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.048
GPT teacher head0.312
Teacher spread0.264 · 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.

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

Citations24
Published2006
Admission routes1
Has abstractyes

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