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Record W4380521104 · doi:10.6000/1929-4409.2020.09.42

Equity in Admissions Policies of Undergraduate Students in Post Democracy in Selected South African Universities

2022· article· en· W4380521104 on OpenAlexvenueno aff
David Matsepe, Michael Cross, Samuel Fenyane

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsnot available
Fundersnot available
KeywordsRedressAffirmative actionEquity (law)DemocracyWarrantSocial justiceHigher educationAccess to Higher EducationContext (archaeology)Political scienceEconomic JusticeEconomic growthSociologySocial classPublic relationsPublic administrationSocial sciencePoliticsLawEconomics

Abstract

fetched live from OpenAlex

This paper investigates the policy pathways that inform and regulate student selection and admission at three selected universities in South Africa, namely the University of the Witwatersrand, the University of Cape Town and the University of KwaZulu-Natal. We argue that these universities have progressed a long way in addressing the race problem in their enrolment strategies. However, their main target group remains students from rich or affluent communities, to the exclusion of potentially good students from marginalised groups, particularly those from under-resourced township and rural schools. As a result, their main challenge in the context of formal access to higher education in South Africa has largely shifted from a race problem to one of social class. This is due to an overemphasis on narrow conceptions of merit that cannot be reconciled with equity and social justice concerns. The paper suggests that current notions of merit warrant reconceptualization in order to embrace these missing dimensions. While there is plenty of evidence that most institutions agree on the need to embrace a particular form of affirmative action to address current social imbalances, given the fierce contestation of redress policies within the South African higher education sector, they find it difficult to develop and implement adequate admission strategies in practice.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.418
Teacher spread0.347 · 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 designObservational
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

Citations4
Published2022
Admission routes1
Has abstractyes

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