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Record W2949095727 · doi:10.16995/lefou.59

Culture as Imperial Synapse: Pre- and Post-Foucauldian Approaches to Culture in British Imperial Historiography

2019· article· en· W2949095727 on OpenAlexaff
Darren Reid

Bibliographic record

VenueLe foucaldien · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHistoriographyCulturalismImperial unit systemMaterialismHistoryField (mathematics)Order (exchange)SociologyEpistemologyPhilosophyAncient historyEmpireLawArchaeologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The study of British imperial culture is heavily attributed to the field of "new imperial history" that became defined in the 1990s, yet theories of imperial cultures date back to at least the 1950s. Furthermore, a recent cadre of new imperial historians has broken away from what might be called "new imperial history proper" to suggest a revised theory of imperial culture. This paper compares the theoretical influences and the methodologies of these three approaches, which I have termed the materialist approach, the discursive approach, and the localized approach, in order to show how pre-Foucauldian and post-Foucauldian imperial histories are not so diametrically opposed between materialism and culturalism as is commonly perceived. Instead, this paper argues that these three approaches all adopt a theory of imperial culture, each different and yet each with its own strengths and weaknesses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.073
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.039
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0020.003
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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2019
Admission routes1
Has abstractyes

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