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Record W3175924501

Locating the Woman: A Note on Customary Law and the Utility of Real Property in the Swaziland Context

2019· article· en· W3175924501 on OpenAlexaff
Tenille E. Brown

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIndigenousContext (archaeology)Land lawProperty lawProperty (philosophy)Political scienceLawReal propertyProperty rightsCultural propertyCommon lawCorporate governanceLand tenureLaw and economicsSociologyGeographyBusinessCultural heritage
DOInot available

Abstract

fetched live from OpenAlex

This chapter looks at women, land and property law within the context of Swaziland. In recent years, in common with its’ Southern African neighbours’, Swaziland has seen an increased awareness of land and property security as a gendered issue. In Swaziland, this has resulted in mobilization of feminists to support equality claims to real property and land law in the Roman- Dutch system. I observe that although the promotion of the culturally indigenous has historically been done at the expense of woman’s experience with land and real property, a core opportunity afforded by relying on the self-governance of Swazi law and custom for promoting security of property rights is its ability to situate the woman’s multi-faceted relationship to land within her cultural reality. This observation is particularly important in a legally dualistic society such as Swaziland, where judgements from the High Court operate within an indigenous legal and cultural context. Ultimately the chapter explores the importance of grounded research in the interaction between law & custom and common law in the process of engaging with and realizing rights to property.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.029
Scholarly communication0.0060.006
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.011
GPT teacher head0.280
Teacher spread0.268 · 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 designTheoretical or conceptual
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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicLegal Issues in South AfricaFrench-language works237,207