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Record W4391170140 · doi:10.21083/ajote.v13i1.7589

What newspapers tell us about teacher-on-learner violence in South African schools

2024· article· en· W4391170140 on OpenAlexvenueno aff
Corene De Wet

Bibliographic record

VenueAfrican Journal of Teacher Education · 2024
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperMathematics educationPsychologyPedagogyPolitical scienceSociologyMedia studies

Abstract

fetched live from OpenAlex

This small-scale qualitative study of newspapers’ portrayal of teacher-on-learner violence in South African schools is informed, firstly, by the World Health Organisation’s definition of violence and four of the World Health Organisation’s six main types of violence involving children and, secondly, by John Galtung’s theory of violence. South African media was used as a database for identifying South African English newspaper articles on teacher-on-learner violence. Qualitative content analysis was employed to systematically work through the identified newspaper articles. Five types of direct teacher-on-learner violence were identified: (1) The physical abuse of learners under the pretext of addressing learner misbehaviour; (2) the normalisation of the sexual abuse of learners by their teachers; (3) teachers’ use of words to systematically humiliate and tear down learners; (4) teachers’ negative stereotyping and discrimination of learners belonging to a different race; and (5) teachers’ malicious neglect of their in loco parentis responsibilities. Looking at teacher-on-learner violence through the lens of Galtung’s theory of violence, this study facilitates an understanding of the multi-layered and complex nature of teacher-on-learner violence and contributes to the existing body of knowledge on teacher-on-learner violence.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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.

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

Citations11
Published2024
Admission routes1
Has abstractyes

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