MétaCan
Menu
Back to cohort
Record W2564468797 · doi:10.1080/23323256.2016.1238772

Is it enough to talk of marriage as a process? Legitimate co-habitation in Umlazi, South Africa

2016· article· en· W2564468797 on OpenAlexaff
Mark Hunter

Bibliographic record

VenueAnthropology Southern Africa · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCohabitationSociologyAmbiguityPosition (finance)Order (exchange)Space (punctuation)Gender studiesLawPolitical science

Abstract

fetched live from OpenAlex

Some 65 years ago Radcliffe-Brown wrote that marriage is “not an event or a condition but a developing process.” This position became modified two decades later when John Comaroff and Simon Roberts demonstrated the ambiguity of the process of marriage in order to challenge the dominant “jural” view. This article argues that these insights still hold well, but that in an era of very low marriage rates in Southern Africa the processual approach is in need of revisiting. Based on research in Umlazi township, Durban, it explores the rise of legitimate co-habitation whereby relatively small amounts of bridewealth-related payments can enable a couple to live together. Such relations are located in what appears to be a growing social space between “full” marriage and ukukipita, a term suggesting illegitimate cohabitation. Instead of evaluating legitimate cohabitation in terms of whether or not it represents a road to marriage, the article stresses how it reconfigures gender and family relationships and enables access to land and housing. The article concludes that marriage remains a critical symbolic marker in all relationships, but that South Africans are finding innovative ways to cohabit.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.024
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.380
Teacher spread0.339 · 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 designQualitative
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

Citations47
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAnthropology Southern AfricaSame topicLegal Issues in South AfricaFrench-language works237,207