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Record W2128955873 · doi:10.1017/s0001972012000320

SITTING AND STANDING: HOW FAMILIES ARE FIXING TRUST IN UNCERTAIN TIMES

2012· article· en· W2128955873 on OpenAlexaff
Elizabeth Cooper

Bibliographic record

VenueAfrica · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsKinshipSolidarityReciprocity (cultural anthropology)PovertySociologySittingLivelihoodEconomic growthPolitical scienceSocioeconomicsGender studiesGeographySocial scienceMedicine

Abstract

fetched live from OpenAlex

ABSTRACT There is widespread apprehension about the resilience of the ‘traditional African’ model of the extended family in maintaining norms and practices of inter-group cooperation and care in conditions of demographic, social and economic change. In Nyanza Province, Kenya, where one of every five children is currently orphaned, and HIV/AIDS and wide-scale poverty continue to render lives and livelihoods insecure, many people are not able to take their families' care for granted. Ideas and practices of kinship have been challenged profoundly by questions regarding who is responsible for the care of orphaned children. This article looks at two complementary practices among Luo families in western Kenya that address such dilemmas: the communal initiative of ‘sitting’ as a family to discuss and resolve issues in a cooperative and consensual manner; and the individualistic initiative of ‘standing’ to represent the interests of another individual. I suggest that while the immediate purposes of sitting and standing are pragmatic in assigning caring responsibilities for specific children, their eventfulness also actualizes something greater: trust, reciprocity and solidarity among extended families.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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

Citations22
Published2012
Admission routes1
Has abstractyes

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