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Record W7133032279

Gender stereotypes in South African law: Hugo and beyond

2003· dissertation· W7133032279 on OpenAlexaffabout
Linda Naidoo

Bibliographic record

VenueTSpace · 2003
Typedissertation
Language
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsBibliothèque et Archives nationales du QuébecBibliographical Society of CanadaUniversity of Ottawa
Fundersnot available
KeywordsStereotype (UML)Stereotype threatNatural (archaeology)Gender equalityTerm (time)Racism
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the extent and effects of gender stereotyping in South African equality law. In using the case of Hugo v the Republic of South Africa, I argue that the stereotype that women are the natural caretakers of children and that men are not has the undesirable impact of preventing the attainment of substantive equality. This stereotype is only one aspect preventing the attainment of substantive equality. Racial stereotypes also exist. These problems are not peculiar to South Africa and are similarly evidenced in Canada. It is argued that benefits to women ought to be framed in terms of functional categories. This combined with a progressive court and long term social policies would bring about substantive equality to women.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.022
Scholarly communication0.0040.005
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.029
GPT teacher head0.350
Teacher spread0.321 · 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
Published2003
Admission routes2
Has abstractyes

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