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Record W2889532384 · doi:10.17159/2223-0386/2018/n18a4

A comparative investigation into the representation of Russia in apartheid and post-apartheid era South African History textbooks

2018· article· en· W2889532384 on OpenAlexaff
Tarryn Halsall

Bibliographic record

VenueYesterday and Today · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsRepresentation (politics)Political scienceGender studiesHistorySociologyLawPolitics

Abstract

fetched live from OpenAlex

In this comparative study we employed a quantitative approach, underpinned by the interpretivist paradigm, to analyse the content on Russia as found in Apartheid and post-Apartheid History textbooks. This was done by means of qualitative content analysis. The focus of the analysis was exclusively on the historical content or substantive knowledge as it related to Russia. What emerged was that the political eras Russia was studied under remained remarkably similar across the Apartheid and post-Apartheid eras. However, clear discernible similarities and differences were otherwise detectable. While big men dominated the content of both eras the approach adopted by the post-Apartheid era History textbooks towards them were generally more critical. While a fear of Communism was imbedded in the Apartheid era History textbooks, the opposite can be said of the post-Apartheid era textbooks. What this points to is that during both political eras the content on Russia was adapted to suit the prevailing identity politics, national narratives and ideology of the time -closed and insular under Apartheid and open and critical in the post-Apartheid era.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.516
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.103
GPT teacher head0.352
Teacher spread0.248 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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