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Record W4231527914 · doi:10.18432/ari29333

Praye(red)

2018· article· en· W4231527914 on OpenAlexvenueno aff
Les Delgado

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryFeelingQueerSadnessIdentity (music)AutoethnographyTragedy (event)AestheticsPrideSociologyAngerEmbodied cognitionVitalityPsychologyGender studiesSocial psychologyPsychoanalysisArtLiteraturePhilosophyEpistemology

Abstract

fetched live from OpenAlex

This performance uses a poem autoethnographically to engage the poet-researcher’s lived experiences in order to examine the relationship of their identity intersections (queer, Latinx, gender non-comforming) to their culture(s) through the current events that inform their experiences and identities. Identifying as gender non-comforming, the poet uses terms like “Latinx” and the pronoun “they” to simply state and relate to a line of Sylvia Plath’s the Bell Jar that “I am, I am, I am.” The usage of literature helps the poet become aware of what they are feeling. Using poetic autoethnography, these pieces strive to amplify the emotions—sadness, anger, anxiety, and fear—that stem from their positionality in relation to events like the tragedy in Orlando. Further, using poetry to engage in embodied and often hidden epistemic realities, the poet looks to the relationship of identity, culture, and the gender/queer, Latinx body that carries this cumulative knowledge from lived experience to lived experience to express those feelings. Using these poetic connections, the poet strives to question their existence in the current world, and make sense of their authenticity.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1190.002

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 head0.146
GPT teacher head0.375
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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