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Record W2954769646 · doi:10.18357/jcs442201919057

Sympoetics of Place and the Red Dust of India

2019· article· en· W2954769646 on OpenAlexvenueno aff
Alex Berry

Bibliographic record

VenueJournal of Childhood Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsnot available
Fundersnot available
KeywordsImpermanenceEthnographyEphemeral keySociologyAestheticsTRACE (psycholinguistics)PoetryVisual artsMedia studiesHistoryArtLiteratureAnthropologyArchaeologyLinguistics

Abstract

fetched live from OpenAlex

Experimenting with forms that lie outside the boundaries of traditional ethnographic research, in this paper I think with Haraway’s (2016) notion of sympoiesis as a platform to reimagine my engagements with place after recently returning home from my pedagogical work as visiting artist-researcher-teacher at a school in Goa, India. I imagine sympoetics as methodological engagement that conceives poetry, not as a purely individual, reflective practice, but rather a co-compositional performance that attends to the polymorphic, often contradictory relations of humans and materials as they are entwined with place. Following the ephemeral movements of India’s red dust, I attend to the intersections of seemingly disparate materials, specifically a child’s pencil and waste materials, and the ways in which they gather meaning together/apart among local/global red dust assemblages. By highlighting and decentering colonial undertones in ethnographic methodology with children and attending closely to anticolonial stories told through my relations with the red dust of India, this paper works to both sit with—and stir up—discomfort, toward more complex, contentious, and responsive accountabilities with place. Using sympoetics to trace the movements and impermanence of red dust, this performance is intentionally partial and aims to situate research in the midst of “not yet” and unknowability.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.533
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.309
Teacher spread0.289 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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