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How Young South Africans Spend their Time

2005· article· en· W2050537175 on OpenAlexvenueno aff
Martin Wittenberg

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyPunctualityUnemploymentWork (physics)AttendanceTruancyYouth unemploymentEconomic growthUnderemploymentCompulsory educationPolitical scienceDemographic economicsGeographyPsychologyEconomicsCriminology

Abstract

fetched live from OpenAlex

South African youth are growing up in a society which is markedly different from that of their elders. The transition to democracy in 1994 has brought with it exciting opportunities and challenges, but youth unemployment has also rocketed during the 1990s. A lot of research and policy work has focused on how to improve the South African education system. The role of the learners in this process has thus far not been scrutinised. This paper examines young people’s educational choices, using South Africa’s Time Use Survey, a nationally representative survey conducted in 2000.We show that attendance is far from universal, even in the age ranges where attendance is supposed to be compulsory. It seems that it is particularly poor in the farming areas. In addition, we suggest that punctuality seems to be an issue.Furthermore we show that around thirty percent of learners seem to arrive at school without having eaten breakfast. This pattern may be related both to poverty and to dieting among teenage girls. Differences between girls and boys show up in other areas also. Girls are expected to perform more chores than boys and as a consequence spend less time in leisure pursuits.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.309
Teacher spread0.275 · 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 designNot applicable
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

Citations5
Published2005
Admission routes1
Has abstractyes

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