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Record W1520132842 · doi:10.7202/1021917ar

Recognition of Prior Learning as “Radical Pedagogy”: A case study of the Workers' College in South Africa

2014· article· en· W1520132842 on OpenAlexvenueno aff
Mphutlane wa Bofelo, Anitha Shah, Kessie Moodley, Linda Cooper, Barbara Jones

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsDignityPedagogySociologyCritical pedagogyPhilosophy of educationFocus groupHigher educationPolitical scienceLawAnthropology

Abstract

fetched live from OpenAlex

This article argues that the model of Recognition of Prior Learning (RPL) in use at the Workers’ College in South Africa may be seen as a form of “radical pedagogy.” Drawing on documentary sources, focus group interviews with staff, and observations, it describes an educational philosophy which aims to build the competencies of activists in labour and community organizations, facilitate their self-affirmation and dignity, and provide an access route to post-school education. It documents and attempts to theorize how this philosophy is enacted in classroom pedagogy, and explores some of the tensions and contradictions encountered. It concludes by acknowledging the unique contribution of these educational practices to an understanding of what RPL as radical pedagogy might look like.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0280.013
Scholarly communication0.0050.004
Open science0.0020.006
Research integrity0.0030.005
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 head0.318
GPT teacher head0.469
Teacher spread0.151 · 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 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

Citations8
Published2014
Admission routes1
Has abstractyes

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