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Record W3014377077 · doi:10.30965/23642807-00502008

Imagining Borders, Imagining Relationships

2020· article· en· W3014377077 on OpenAlexaff
Héctor A. Acero-Ferrer

Bibliographic record

VenueInterdisciplinary Journal for Religion and Transformation in Contemporary Society · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsNarrativeIdeologySociologyAestheticsEpistemologyUtopiaAction (physics)PoliticsPolitical scienceLawLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract Conceptualizations of human borders will often refer to narratives of encounters, exchanges, and/or interactions that take place in two different but interrelated settings: one internal, between individuals or groups belonging to the space defined by the border; and one external, between such individuals or collectives and everything that is foreign to them. This integrating/distinguishing role of narratives underscores the imaginative process through which borders emerge, expressed with great poignancy in the fluidity and complexity of border-setting practices in late-modern societies. Paul Ricœur’s take on collective imagination and human action can be a tool to unearth some of the key conceptual features of such integration-distinction tension, by pointing to ways in which social imaginaries shape the liquidity and modality of borders in increasingly diverse communities. Ricœur’s analysis of the development of cultural imaginaries through the opposed yet complementary forces of ideology and utopia, and his exploration of the multi-layered character of mutual recognition, come together in an understanding of human persons – and communities – capable of imagining enlarged spaces of recognition. Richard Kearney complements this analysis with an account of narrative imagination that allows one to articulate the narrative origins of concrete human realities and practices, such as borders and border-setting. In this article, I make use of the contributions of Ricœur and Kearney to argue that a clear understanding social imagination is needed in order to account for the cultural matrix set by human borders, as well as to provide answers to the practical questions raised by concrete historical examples of borders and border-setting.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.096
GPT teacher head0.333
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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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