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Record W4284895291 · doi:10.5195/errs.2022.578

At the Limits of Narrative. Unintelligibility and the (Im)possibilities of Self-Disclosure in the Asylum Claiming Process.

2022· article· en· W4284895291 on OpenAlexaff
Lucie Robathan

Bibliographic record

VenueÉtudes Ricoeuriennes / Ricoeur Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsMcGill University
Fundersnot available
KeywordsNarrativityNarrativeSubjectivityHermeneuticsSubject (documents)EpistemologySociologyIdentity (music)PoliticsNarrative identityAestheticsTransformative learningNarrative inquiryPower (physics)Narrative criticismPhilosophyPolitical scienceLawLinguisticsComputer science

Abstract

fetched live from OpenAlex

This paper offers an intervention into the notion of narrativity. It aims to refract Ricœur’s hermeneutics of the subject through a more expanded account of the political dimension of narrative, both to situate the narrative self politically, and to flesh out the ethico-political (im)possibilities of self-disclosure. Focusing on the process of claiming asylum as an instance of politically precarious self-disclosure in which narrative is demanded as a marker of truthful identity, it will explore the limits of narrative as the mode through which subjectivity is made intelligible. Through an analysis of the residues of power in the institution of language that qualify the emergence of the speaking subject and the socio-political assumptions we can excavate from the notion of narrative time, this paper will suggest that narrative unintelligibility could have politically transformative potential.

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)0.009
metaresearch head score (Gemma)0.016
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 score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.052
Scholarly communication0.0100.010
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.298
Teacher spread0.249 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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