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Record W4244836394 · doi:10.1017/9781108635042

Deparochializing Political Theory

2020· book· en· W4244836394 on OpenAlexaff
Melissa S. Williams

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoliticsComputer scienceLibrary sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

In a world no longer centered on the West, what should political theory become? Although Western intellectual traditions continue to dominate academic journals and course syllabi in political theory, up-and-coming contributions of 'comparative political theory' are rapidly transforming the field. Deparochializing Political Theory creates a space for conversation amongst leading scholars who differ widely in their approaches to political theory. These scholars converge on the belief that we bear a collective responsibility to engage and support the transformation of political theory. In these exchanges, 'deparochializing' political theory emerges as an intellectual, educational and political practice that cuts across methodological approaches. Because it is also an intergenerational project, this book presses us to re-imagine our teaching and curriculum design. Bearing the marks of its beginnings in East Asia, Deparochializing Political Theory seeks to de-center Western thought and explore the evolving tasks of political theory in an age of global modernity.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.002

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 head0.030
GPT teacher head0.267
Teacher spread0.237 · 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 designTheoretical or conceptual
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

Citations41
Published2020
Admission routes1
Has abstractyes

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