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Record W4399082080 · doi:10.1515/iph-2024-2004

Decolonizing Through Public History – Introduction

2024· article· en· W4399082080 on OpenAlexaboutno aff
Thomas Cauvin

Bibliographic record

VenueInternational Public History · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
FundersFonds National de la Recherche Luxembourg
KeywordsDecolonizationPublic historyColonialismRepatriationContext (archaeology)InstitutionPublic spaceHistoryPolitical historyPolitical scienceSociologySocial scienceMedia studiesLawArchaeologyPolitics

Abstract

fetched live from OpenAlex

Abstract Decolonization is the subject of an abundant literature, both as a historical event and as a contemporary process. In relations with the past, debates have risen about issues such as colonial monuments, museum collections, and repatriation. Rather than dealing with a specific type of space, institution, or material, this special issue in International Public History offers a discussion on the many links between decolonization and public history. The articles explore if and to what extent public history practices can contribute to decolonizing the history production process (through decolonized sources, decolonized interpretation processes, and decolonized space of communication of history). The articles discuss what ‘public’ in ‘public history’ means: who is doing history, for whom, with whom, and for what? The self-reflective approach of public history also questions the colonial bias and processes at stake in institutions such as archives, museums, and universities. The special issue includes contributions from various countries (South Africa, Kenya, Brazil, Canada, and Japan) to foster discussions on the plurality of links between public history and decolonization in an international context that goes beyond the too-often Western oriented public history frameworks.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.082
GPT teacher head0.312
Teacher spread0.230 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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