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Record W2171918329 · doi:10.1177/0090591708329650

Disability, Self Image, and Modern Political Theory

2008· article· en· W2171918329 on OpenAlexaff
Barbara Arneil

Bibliographic record

VenuePolitical Theory · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPoliticsPersonhoodSociologyOpposition (politics)Political philosophyAutonomyBinary oppositionIdentity (music)SelfCitizenshipEpistemologyLawAestheticsPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Charles Taylor argues that recognition begins with the politics of “self-image,” as groups represented in the past by others in ways harmful to their own identity replace negative historical self-images with positive ones of their own making. Given the centrality of “self image” to his politics of recognition, it is striking that Taylor, himself, represents disabled people in language that is both limiting and depreciating. The author argues such negative self-images are not unique to Taylor but endemic to modern political thought from John Locke to John Rawls, as the disabled (“irrational” and/or mentally disabled/ill people) are constituted in direct opposition to the rational person and/or citizen. Using contemporary social theories of disability, as articulated by disabled scholars and advocates, the author concludes that such negative self-images (and the binary of autonomy/justice and dependency/charity underpinning them) must be purged from political theory and replaced with an alternative theory of personhood/citizenship rooted in the image of interdependency.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.033
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.347
Teacher spread0.316 · 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
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

Citations124
Published2008
Admission routes1
Has abstractyes

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