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Record W4306153816 · doi:10.1017/s002185372200055x

Wise Mothers and Wise Buyers: Marketing Tea and Home Improvement in 1930s South Africa

2022· article· en· W4306153816 on OpenAlexfundno aff
Katie Carline

Bibliographic record

VenueThe Journal of African History · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCollege of Engineering, Michigan State University
KeywordsNewspaperConsumption (sociology)CommercializationLiteracyXhosaAdvertisingPolitical scienceMarketingSociologySocial scienceBusinessLaw

Abstract

fetched live from OpenAlex

Abstract Histories of advertising in Africa focus on the postwar and postcolonial periods. This essay examines an innovative marketing campaign in South Africa's eastern Cape in the 1930s. The campaign reveals congruence and conflict between increased marketing of consumer goods to African households and the contemporaneous growth of women's home improvement societies. The newspaper Umlindi we Nyanga used testimonials and written competitions to sell its Ambrosia brand of tea to rural women. Advertisers and consumers drew on local meanings of tea consumption and debates about feminine respectability to present tea-drinking women as ‘intelligent’ and ‘wise mothers’. The emphasis on intelligence linked tea to literacy, in part because text-based consumer culture offered rural women a way to visibly consume socially respectable goods. The essay concludes with a close examination of two testimonials written by leaders of home improvement societies, which hint at the contradictions implicit in the commercialization of the ‘wise mother’.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.016
GPT teacher head0.217
Teacher spread0.201 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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