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Record W1521088803 · doi:10.20355/c5xw2d

Unhu/Ubuntu and Education for Reconciliation in Zimbabwe

2013· article· en· W1521088803 on OpenAlexaffvenue
Oswell Hapanyengwi-Chemhuru, Edward Shizha

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican cultural and philosophical studies
Canadian institutionsWilfrid Laurier UniversityUniversity of Alberta
Fundersnot available
KeywordsDignityIndependence (probability theory)Promotion (chess)Argument (complex analysis)SociologyDiversity (politics)Political scienceEnvironmental ethicsLawPhilosophy

Abstract

fetched live from OpenAlex

The paper examines the concept, strengths and shortcomings, role and implementation of the reconciliation policy as Zimbabwe emerged from periods of conflict crisis soon after independence in the 1980s, and the current crisis in the 2000s and how the policy can be introduced in schools through ‘education for reconciliation’. The authors argue that education can be used to cultivate reconciliation and national healing in the evidently ‘wounded’ people of Zimbabwe who bear scars of colonial times and war, and the post-independence conflicts. Reconciliation through education for “diversity” and tolerance makes a compelling argument in so far as we understand how education shapes culture and cultivates values among a people. Education for reconciliation is perceived as a philosophy that promotes respect for human life and human dignity. The paper concludes that education is an instrument for the inculcation and promotion of the epistemic and ontological principles enshrined in the African philosophy of Ubuntu/unhu.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0040.003
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.363
Teacher spread0.315 · 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

Citations17
Published2013
Admission routes2
Has abstractyes

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