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Record W4310251553 · doi:10.1386/peet_00042_1

Caring for our futures: Epistolary praxis and the promise of slow

2022· article· en· W4310251553 on OpenAlexaboutno aff
Rachel Epp Buller

Bibliographic record

VenuePerforming Ethos International Journal of Ethics in Theatre and Performance · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsnot available
Fundersnot available
KeywordsPraxisActive listeningFutures contractReading (process)Visual artsPoetryEmbodied cognitionLiteratureAestheticsHistoryArtSociologyLinguisticsEpistemologyCommunicationPhilosophy

Abstract

fetched live from OpenAlex

This creative–critical article advocates for the promise of letters in imagining possible futures. The piece includes ten of my Letters to the Future, epistolary poems written as fictocritical conversations between the texts that I read and imagined future readers. In the letters, I write of listening and care, patterns and methods of making passed between our hands, embodied forms of knowledge and slow practices, as I imagine and speak to our future caring communities. The letters are interspersed with short scholarly reflections on feminist epistolary history, traditions of matrilineal knowledge and slow reading as maternal performance. As part of my multimodal research-creation project on listening as artistic practice, this epistolary work takes visual form in drawings, paper-cut installations and letterpress prints, exhibited most recently at the University of Alberta in 2022.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0140.021
Scholarly communication0.0110.008
Open science0.0010.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.046
GPT teacher head0.366
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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