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Record W4384833052 · doi:10.6018/ijes.542731

Deluge of Affects

2023· article· en· W4384833052 on OpenAlexfundno aff
Eva Darias-Beautell

Bibliographic record

VenueInternational Journal of English Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
FundersUniversity of TorontoUniversidad de La Laguna
KeywordsPityShameEmbarrassmentMaterialismFeelingEmpathyCompassionPsychoanalysisAestheticsAffect (linguistics)PsychologySociologySocial psychologyArtPhilosophyEpistemologyCommunicationTheology

Abstract

fetched live from OpenAlex

This article examines Elle-Máijá Tailfeathers and Kathleen Hepburn’s film The Body Remembers When the World Broke Open (2019) through the lens of materialist and feminist affect theories as they intersect with critical Indigeneity. It investigates how the film produces two parallel and conflicting reactions in the viewer, for whom “ugly feelings” (Ngai, 2007), such as failure, embarrassment, pity or shame, compete with an overwhelming and often frustrated need for empathy and compassion.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.020
Scholarly communication0.0090.007
Open science0.0000.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.053
GPT teacher head0.406
Teacher spread0.352 · 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
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
Published2023
Admission routes1
Has abstractyes

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