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Record W4252971843 · doi:10.1093/bjsw/bcab222

A reinterrogation of South African child welfare discourse: A case for decolonisation?

2021· article· en· W4252971843 on OpenAlexaffabout
Jeanette Schmid

Bibliographic record

VenueThe British Journal of Social Work · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsDecolonizationWelfareIndigenousColonialismSociologyPunitive damagesStatutory lawPolitical scienceGender studiesWelfare reformPolitical economyLawPolitics

Abstract

fetched live from OpenAlex

Abstract Relying on discourse analysis and critical social work, this article explores the relevance of a decolonisation discourse to South African child welfare. A child welfare discourse of coloniality emerges from Australia, New Zealand and Canada. This emphasises the role that colonisation has played in eradicating indigenous persons or alternately assimilating subjugated populations to Western norms and sensibilities and maintains that coloniality persists in contemporary child welfare. South African child welfare has not been explicitly problematised as furthering coloniality. There have been transformation efforts post-apartheid relating to the legislative/policy environment and increasing racial representation and community-based access. However, the colonial and apartheid roots of South African child welfare persist in impacting child welfare, particularly by overriding local ways of being. A decolonisation discourse is needed to identify the various ways in which the child welfare system replicates colonising processes and how these can be interrupted. To do so, the individualised, intrusive, punitive, statutory Child Protection discourse must be replaced, structural issues prioritised, intergenerational and contemporary trauma centred, liberatory indigenous child-rearing practices privileged and local knowledges curated and used to inform the child welfare process.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.997

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 studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.387
Teacher spread0.352 · 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 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

Citations3
Published2021
Admission routes2
Has abstractyes

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