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Record W2037183540 · doi:10.1080/01916599.2013.768004

Telling Contested Stories: J. G. A. Pocock and Paul Ricoeur

2013· article· en· W2037183540 on OpenAlexafffund
Kenneth Sheppard

Bibliographic record

VenueHistory of European Ideas · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsConcordia University
FundersConcordia University
KeywordsNarrativeHistoriographyAutonomyIdentity (music)SociologyMeaning (existential)Representation (politics)PluralOpenness to experienceEpistemologyAestheticsSet (abstract data type)Ideal (ethics)LinguisticsPhilosophyPsychologySocial psychologyLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

SummaryThis paper traces a mutually reinforcing set of arguments about the practice of history in the work of J. G. A. Pocock and Paul Ricoeur that responds to challenges posed to the autonomy of selves and their communities raised by both thinkers. It begins with their respective views on language, texts and actions, moves to the construction of narrative and historiography, and concludes with their account of selves and the communities to which they belong. Corresponding to these three considerations are a set of conclusions drawn with different emphases: first, that both texts and acts are potentially open to indefinite and plural interpretations; second, that narrative and historiography are constitutively contested modes of critical discourse continually open to the construction of new meaning; and third, that the contested, capable, narrative self, and the community to which that mediated self belongs, exercises autonomy as an active, responsible, reflective citizen and/or critical historian. It concludes from this study that the limited openness of language, narrative and identity constitutes the promise and risk of history as a contested and affective representation.

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)0.008
metaresearch head score (Gemma)0.015
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.021
Scholarly communication0.0120.011
Open science0.0010.004
Research integrity0.0040.004
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 head0.038
GPT teacher head0.201
Teacher spread0.163 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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