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A Pedagogy of Erasure

2024· book-chapter· en· W4392936260 on OpenAlexaffabout
Hayden King, David P. Thomas

Bibliographic record

VenueOxford University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsMount Allison UniversityToronto Metropolitan University
Fundersnot available
KeywordsIndigenizationIndigenousSilenceCurriculumDecolonizationContext (archaeology)PedagogySociologyPoliticsPolitical scienceLawAnthropologyGeographyAestheticsArt

Abstract

fetched live from OpenAlex

Abstract This chapter critically analyzes the near silence from international relations scholars on the topics and perspectives of Indigenous peoples in relation to the study of global politics. In the broader context of this silence in the discipline, and the calls for post-secondary institutions to engage in processes of Indigenization or decolonization, this chapter focuses specifically on how IR is taught at the introductory level in Canada. It asks, Are IR teachers integrating Indigenous perspectives and content into the curriculum or following the stubborn trend of continuing to erase Indigenous people and perspectives? To answer the question, the authors have undertaken content analysis of 42 introductory IR course outlines from across Canada. Despite some signs of hope in the data, they reveal that the teaching of IR at the introductory level in Canada fails to adequately respond to these pressing calls to decolonize the curriculum.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.985
Threshold uncertainty score0.649

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 studies0.0000.000
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 head0.288
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2024
Admission routes2
Has abstractyes

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